Remove TfNative Smart-Dim model and code-path

Remove kUserActivityPredictionMlService that is launched to 'true'.

* Remove feature flag
* Remove UI for feature flag (about_flags)
* Remove code paths followed in the 'false' case.
* Remove TfNative generated code and preprocessor config.
* Update unit tests.

Bug: 893425, 942934
Change-Id: I14e40e3cee0e8285f9f2bd018a9830e7071d8084
Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/1605585
Commit-Queue: Andrew Moylan <amoylan@chromium.org>
Reviewed-by: calamity <calamity@chromium.org>
Reviewed-by: Jia Meng <jiameng@chromium.org>
Cr-Commit-Position: refs/heads/master@{#661273}
diff --git a/chrome/browser/about_flags.cc b/chrome/browser/about_flags.cc
index 984352f..e4416847 100644
--- a/chrome/browser/about_flags.cc
+++ b/chrome/browser/about_flags.cc
@@ -3510,13 +3510,6 @@
      flag_descriptions::kWebrtcHwVP9EncodingDescription, kOsCrOS,
      FEATURE_VALUE_TYPE(features::kWebRtcHWVP9Encoding)},
 
-#if defined(OS_CHROMEOS)
-    {"user-activity-prediction-ml-service",
-     flag_descriptions::kUserActivityPredictionMlServiceName,
-     flag_descriptions::kUserActivityPredictionMlServiceDescription, kOsCrOS,
-     FEATURE_VALUE_TYPE(chromeos::features::kUserActivityPredictionMlService)},
-#endif  // defined(OS_CHROMEOS)
-
 #if defined(OS_ANDROID)
     {"manual-password-generation-android",
      flag_descriptions::kManualPasswordGenerationAndroidName,
diff --git a/chrome/browser/browser_resources.grd b/chrome/browser/browser_resources.grd
index a206791..c51dad9 100644
--- a/chrome/browser/browser_resources.grd
+++ b/chrome/browser/browser_resources.grd
@@ -708,7 +708,6 @@
         <include name="IDR_TAB_RANKER_EXAMPLE_PREPROCESSOR_CONFIG_PB" file="resource_coordinator\tab_ranker\example_preprocessor_config.pb" type="BINDATA" />
       </if>
       <if expr="chromeos">
-        <include name="IDR_SMART_DIM_EXAMPLE_PREPROCESSOR_CONFIG_PB" file="chromeos\power\ml\smart_dim\example_preprocessor_config.pb" type="BINDATA" />
         <include name="IDR_SMART_DIM_LITE_EXAMPLE_PREPROCESSOR_CONFIG_PB" file="chromeos\power\ml\smart_dim\lite_example_preprocessor_config.pb" type="BINDATA" />
       </if>
       <if expr="chromeos">
diff --git a/chrome/browser/chromeos/power/ml/smart_dim/BUILD.gn b/chrome/browser/chromeos/power/ml/smart_dim/BUILD.gn
index ee0161b..5677814 100644
--- a/chrome/browser/chromeos/power/ml/smart_dim/BUILD.gn
+++ b/chrome/browser/chromeos/power/ml/smart_dim/BUILD.gn
@@ -3,7 +3,6 @@
 # found in the LICENSE file.
 
 source_set("smart_dim") {
-  # Dependent targets should not include tf_native_inference.h directly.
   public = [
     "model.h",
     "model_impl.h",
@@ -12,9 +11,9 @@
   sources = [
     "ml_service_client.cc",
     "ml_service_client.h",
+    "model.h",
     "model_impl.cc",
-    "tf_native_inference.cc",
-    "tf_native_inference.h",
+    "model_impl.h",
   ]
 
   deps = [
diff --git a/chrome/browser/chromeos/power/ml/smart_dim/example_preprocessor_config.pb b/chrome/browser/chromeos/power/ml/smart_dim/example_preprocessor_config.pb
deleted file mode 100644
index 94d19a0..0000000
--- a/chrome/browser/chromeos/power/ml/smart_dim/example_preprocessor_config.pb
+++ /dev/null
Binary files differ
diff --git a/chrome/browser/chromeos/power/ml/smart_dim/model_impl.cc b/chrome/browser/chromeos/power/ml/smart_dim/model_impl.cc
index 7bce399..8b7eb80 100644
--- a/chrome/browser/chromeos/power/ml/smart_dim/model_impl.cc
+++ b/chrome/browser/chromeos/power/ml/smart_dim/model_impl.cc
@@ -18,7 +18,6 @@
 #include "base/strings/string_number_conversions.h"
 #include "base/task/post_task.h"
 #include "base/task_runner_util.h"
-#include "chrome/browser/chromeos/power/ml/smart_dim/tf_native_inference.h"
 #include "chrome/browser/chromeos/power/ml/user_activity_ukm_logger_helpers.h"
 #include "chrome/grit/browser_resources.h"
 #include "chromeos/constants/chromeos_features.h"
@@ -39,14 +38,10 @@
 // RankerExample to a vectorized float for inactivity score calculation. Returns
 // nullptr if cannot load or parse the config.
 std::unique_ptr<assist_ranker::ExamplePreprocessorConfig>
-LoadExamplePreprocessorConfig(bool use_ml_service) {
+LoadExamplePreprocessorConfig() {
   auto config = std::make_unique<assist_ranker::ExamplePreprocessorConfig>();
 
-  // TODO(crbug.com/893425): Remove the TF Native version once we shift to
-  // ML service completely.
-  const int res_id = use_ml_service
-                         ? IDR_SMART_DIM_LITE_EXAMPLE_PREPROCESSOR_CONFIG_PB
-                         : IDR_SMART_DIM_EXAMPLE_PREPROCESSOR_CONFIG_PB;
+  const int res_id = IDR_SMART_DIM_LITE_EXAMPLE_PREPROCESSOR_CONFIG_PB;
 
   scoped_refptr<base::RefCountedMemory> raw_config =
       ui::ResourceBundle::GetSharedInstance().LoadDataResourceBytes(res_id);
@@ -238,11 +233,7 @@
 
 }  // namespace
 
-SmartDimModelImpl::SmartDimModelImpl()
-    : blocking_task_runner_(base::CreateSequencedTaskRunnerWithTraits(
-          {base::MayBlock(), base::TaskPriority::USER_VISIBLE})),
-      use_ml_service_(base::FeatureList::IsEnabled(
-          features::kUserActivityPredictionMlService)) {}
+SmartDimModelImpl::SmartDimModelImpl() = default;
 
 SmartDimModelImpl::~SmartDimModelImpl() = default;
 
@@ -282,36 +273,6 @@
   return SmartDimModelResult::kSuccess;
 }
 
-SmartDimModelResult SmartDimModelImpl::CalculateInactivityScoreTfNative(
-    const UserActivityEvent::Features& features,
-    float* inactivity_score_out) {
-  // This is the TF Native codepath.
-  // TODO(crbug.com/893425): Remove this codepath once we shift to ML service
-  // completely.
-  CHECK(inactivity_score_out);
-
-  std::vector<float> vectorized_features;
-  auto preprocess_result = PreprocessInput(features, &vectorized_features);
-  if (preprocess_result != SmartDimModelResult::kSuccess) {
-    LogPowerMLSmartDimModelResult(preprocess_result);
-    return preprocess_result;
-  }
-
-  if (vectorized_features.size() != tfnative_model::FEATURES_SIZE) {
-    LogPowerMLSmartDimModelResult(
-        SmartDimModelResult::kMismatchedFeatureSizeError);
-    return SmartDimModelResult::kMismatchedFeatureSizeError;
-  }
-
-  if (!model_alloc_)
-    model_alloc_ = std::make_unique<tfnative_model::FixedAllocations>();
-
-  tfnative_model::Inference(vectorized_features.data(), inactivity_score_out,
-                            model_alloc_.get());
-
-  return SmartDimModelResult::kSuccess;
-}
-
 UserActivityEvent::ModelPrediction
 SmartDimModelImpl::CreatePredictionFromInactivityScore(float inactivity_score) {
   UserActivityEvent::ModelPrediction prediction;
@@ -329,26 +290,7 @@
   return prediction;
 }
 
-UserActivityEvent::ModelPrediction SmartDimModelImpl::ShouldDimTfNative(
-    const UserActivityEvent::Features& input_features) {
-  UserActivityEvent::ModelPrediction prediction;
-  prediction.set_response(UserActivityEvent::ModelPrediction::MODEL_ERROR);
-
-  float inactivity_score = 0;
-  const SmartDimModelResult result =
-      CalculateInactivityScoreTfNative(input_features, &inactivity_score);
-
-  if (result != SmartDimModelResult::kSuccess) {
-    // No need to log here as all error cases are already logged in
-    // CalculateInactivityScoreTfNative.
-    return prediction;
-  }
-
-  LogPowerMLSmartDimModelResult(SmartDimModelResult::kSuccess);
-  return CreatePredictionFromInactivityScore(inactivity_score);
-}
-
-void SmartDimModelImpl::ShouldDimMlService(
+void SmartDimModelImpl::ShouldDim(
     const UserActivityEvent::Features& input_features,
     DimDecisionCallback callback) {
   UserActivityEvent::ModelPrediction prediction;
@@ -392,15 +334,7 @@
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
   // Cancel previously assigned callbacks and set it to the new callback.
   cancelable_callback_.Reset(std::move(dim_callback));
-  if (!use_ml_service_) {
-    base::PostTaskAndReplyWithResult(
-        blocking_task_runner_.get(), FROM_HERE,
-        base::BindOnce(&SmartDimModelImpl::ShouldDimTfNative,
-                       base::Unretained(this), input_features),
-        base::BindOnce(cancelable_callback_.callback()));
-  } else {
-    ShouldDimMlService(input_features, cancelable_callback_.callback());
-  }
+  ShouldDim(input_features, cancelable_callback_.callback());
 }
 
 void SmartDimModelImpl::CancelPreviousRequest() {
@@ -415,18 +349,13 @@
 }
 
 void SmartDimModelImpl::LazyInitialize() {
-  // TODO(crbug.com/893425): Remove the flag check once we shift to ML service
-  // completely.
-  if (use_ml_service_) {
-    if (!ml_service_client_) {
-      ml_service_client_ = CreateMlServiceClient();
-    }
+  if (!ml_service_client_) {
+    ml_service_client_ = CreateMlServiceClient();
   }
 
-  if (preprocessor_config_)
-    return;
-
-  preprocessor_config_ = LoadExamplePreprocessorConfig(use_ml_service_);
+  if (!preprocessor_config_) {
+    preprocessor_config_ = LoadExamplePreprocessorConfig();
+  }
 }
 
 }  // namespace ml
diff --git a/chrome/browser/chromeos/power/ml/smart_dim/model_impl.h b/chrome/browser/chromeos/power/ml/smart_dim/model_impl.h
index 942b218..ce15296 100644
--- a/chrome/browser/chromeos/power/ml/smart_dim/model_impl.h
+++ b/chrome/browser/chromeos/power/ml/smart_dim/model_impl.h
@@ -22,10 +22,6 @@
 namespace power {
 namespace ml {
 
-namespace tfnative_model {
-struct FixedAllocations;
-}  // namespace tfnative_model
-
 // These values are persisted to logs. Entries should not be renumbered and
 // numeric values should never be reused.
 enum class SmartDimModelResult {
@@ -65,11 +61,8 @@
   void SetMlServiceClientForTesting(std::unique_ptr<MlServiceClient> client);
 
  private:
-  FRIEND_TEST_ALL_PREFIXES(SmartDimTfNativeModelTest, Basic);
-  FRIEND_TEST_ALL_PREFIXES(SmartDimTfNativeModelTest, OptionalFeaturesMissing);
-
   // Loads the preprocessor config if not already loaded. Also initializes the
-  // MlServiceClient object if the ML Service is being used for inference.
+  // MlServiceClient object.
   void LazyInitialize();
 
   // Pre-processes the input features into a vector, placed in
@@ -81,51 +74,27 @@
       const UserActivityEvent::Features& features,
       std::vector<float>* vectorized_features);
 
-  // Calculates inactivity score and returns result status. Also logs the status
-  // to UMA.
-  //
-  // This codepath is used when the inference calls are made to TF-Native.
-  SmartDimModelResult CalculateInactivityScoreTfNative(
-      const UserActivityEvent::Features& features,
-      float* inactivity_score_out);
-
   // Takes an |inactivity_score| returned from the ML model and, using that,
   // returns a ModelPrediction.
   UserActivityEvent::ModelPrediction CreatePredictionFromInactivityScore(
       float inactivity_score);
 
-  // Task which gets posted to the |blocking_task_runner_| and
-  // performs the ML inference call. Based on the result of the inference call,
-  // a prediction is returned, and this return value will be passed to a
-  // DimDecisionCallback which will execute after this function.
-  UserActivityEvent::ModelPrediction ShouldDimTfNative(
-      const UserActivityEvent::Features& input_features);
-
   // Calls the ML service Mojo API to perform an Smart Dim inference call,
   // given |input_features|. The |callback| is supplied to the Mojo API,
   // which in turn will call it to provide the result (a ModelPrediction), once
   // the inference is complete.
-  void ShouldDimMlService(const UserActivityEvent::Features& input_features,
-                          DimDecisionCallback callback);
+  void ShouldDim(const UserActivityEvent::Features& input_features,
+                 DimDecisionCallback callback);
 
   std::unique_ptr<assist_ranker::ExamplePreprocessorConfig>
       preprocessor_config_;
 
-  // Fixed-size working memory provided to the inferencing function. Lazily
-  // initialized once so it isn't reallocated for every inference.
-  std::unique_ptr<tfnative_model::FixedAllocations> model_alloc_;
-
-  // A separate task runner is used to perform the TF Native inference.
-  const scoped_refptr<base::SequencedTaskRunner> blocking_task_runner_;
-
   // Cancelable wrapper for the DimDecisionCallback passed by the client to
   // RequestDimDecision().
   base::CancelableOnceCallback<void(UserActivityEvent::ModelPrediction)>
       cancelable_callback_;
 
-  const bool use_ml_service_;
-  // Pointer to the object that handles the ML service calls. This pointer
-  // is only initialized if features::kSmartDimMLService is set to true.
+  // Pointer to the object that handles the ML service calls.
   std::unique_ptr<MlServiceClient> ml_service_client_;
 
   SEQUENCE_CHECKER(sequence_checker_);
diff --git a/chrome/browser/chromeos/power/ml/smart_dim/model_unittest.cc b/chrome/browser/chromeos/power/ml/smart_dim/model_unittest.cc
index 41a59bd..825baa0 100644
--- a/chrome/browser/chromeos/power/ml/smart_dim/model_unittest.cc
+++ b/chrome/browser/chromeos/power/ml/smart_dim/model_unittest.cc
@@ -25,6 +25,19 @@
 
 namespace {
 
+// Arbitrary inactivity score for the fake ML Service client to return:
+constexpr float kTestInactivityScore = -3.7;
+// Quantized into the range [0, 100] via sigmoid transform:
+constexpr int kQuantizedTestInactivityScore = 2;
+
+// Arbitrary dim thresholds lower/higher than kTestInactivityScore, implying
+// no/yes dim decisions respectively.
+constexpr double kLowDimThreshold = -10.0;
+constexpr double kHighDimThreshold = -0.1;
+// Same values quantized into the range [0, 100] via sigmoid transform:
+constexpr int kQuantizedLowDimThreshold = 0;
+constexpr int kQuantizedHighDimThreshold = 47;
+
 UserActivityEvent::Features DefaultFeatures() {
   UserActivityEvent::Features features;
   // Bucketize to 95.
@@ -64,24 +77,15 @@
  public:
   SmartDimFeatureFlags() = default;
 
-  void Initialize(const bool use_ml_service, const double dim_threshold) {
+  void Initialize(const double dim_threshold) {
     const std::map<std::string, std::string> params = {
         {"dim_threshold", base::NumberToString(dim_threshold)}};
     smart_dim_feature_override_.InitAndEnableFeatureWithParameters(
         features::kUserActivityPrediction, params);
-
-    if (use_ml_service) {
-      ml_service_feature_override_.InitAndEnableFeature(
-          features::kUserActivityPredictionMlService);
-    } else {
-      ml_service_feature_override_.InitAndDisableFeature(
-          features::kUserActivityPredictionMlService);
-    }
   }
 
  private:
   base::test::ScopedFeatureList smart_dim_feature_override_;
-  base::test::ScopedFeatureList ml_service_feature_override_;
 
   DISALLOW_COPY_AND_ASSIGN(SmartDimFeatureFlags);
 };
@@ -97,8 +101,7 @@
       base::RepeatingCallback<UserActivityEvent::ModelPrediction(float)>
           get_prediction_callback,
       SmartDimModel::DimDecisionCallback decision_callback) override {
-    // Corresponds to DefaultFeatures() with TfNativeModel:
-    const float inactivity_score = -3.6615708;
+    const float inactivity_score = kTestInactivityScore;
 
     UserActivityEvent::ModelPrediction model_prediction =
         get_prediction_callback.Run(inactivity_score);
@@ -113,9 +116,7 @@
 
 }  // namespace
 
-// Parameterized test fixture. The bool parameter is whether to test the ML
-// Service codepath. If false, the old TFNative codepath is tested.
-class SmartDimModelImplTest : public testing::TestWithParam<bool> {
+class SmartDimModelImplTest : public testing::Test {
  public:
   SmartDimModelImplTest()
       : scoped_task_environment_(
@@ -126,9 +127,6 @@
   ~SmartDimModelImplTest() override = default;
 
  protected:
-  // More readable name for the test parameter:
-  bool UsesMlService() const { return GetParam(); }
-
   // Sets a fake MlServiceClient into |impl|.
   void InjectFakeMlServiceClient(SmartDimModelImpl* const impl) {
     impl->SetMlServiceClientForTesting(std::make_unique<FakeMlServiceClient>());
@@ -140,55 +138,13 @@
   DISALLOW_COPY_AND_ASSIGN(SmartDimModelImplTest);
 };
 
-// For the TFNative model, test a hard-coded known-good model result.
-TEST(SmartDimTfNativeModelTest, Basic) {
-  base::test::ScopedTaskEnvironment env;
+// With a high dim threshold, NO_DIM decision is expected.
+TEST_F(SmartDimModelImplTest, ShouldNotDim) {
   SmartDimFeatureFlags flags;
-  flags.Initialize(false /* use_ml_service */, -0.1 /* dim_threshold */);
+  flags.Initialize(kHighDimThreshold);
 
   SmartDimModelImpl smart_dim_model;
-
-  float inactivity_score;
-  EXPECT_EQ(SmartDimModelResult::kSuccess,
-            smart_dim_model.CalculateInactivityScoreTfNative(
-                DefaultFeatures(), &inactivity_score));
-  // Score has been calculated outside of chrome.
-  EXPECT_FLOAT_EQ(-3.6615708, inactivity_score);
-}
-
-// For the TFNative model, test a known-good result with empty features.
-TEST(SmartDimTfNativeModelTest, OptionalFeaturesMissing) {
-  base::test::ScopedTaskEnvironment env;
-  SmartDimFeatureFlags flags;
-  flags.Initialize(false /* use_ml_service */, -0.1 /* dim_threshold */);
-
-  SmartDimModelImpl smart_dim_model;
-
-  UserActivityEvent::Features features = DefaultFeatures();
-  features.clear_battery_percent();
-  features.clear_time_since_last_key_sec();
-  features.clear_time_since_last_mouse_sec();
-  features.clear_time_since_video_ended_sec();
-  features.clear_source_id();
-  features.clear_has_form_entry();
-  features.clear_engagement_score();
-  features.clear_tab_domain();
-
-  float inactivity_score;
-  EXPECT_EQ(SmartDimModelResult::kSuccess,
-            smart_dim_model.CalculateInactivityScoreTfNative(
-                features, &inactivity_score));
-  // Score has been calculated outside of chrome.
-  EXPECT_FLOAT_EQ(-1.9680425, inactivity_score);
-}
-
-TEST_P(SmartDimModelImplTest, ShouldNotDim) {
-  SmartDimFeatureFlags flags;
-  flags.Initialize(UsesMlService(), -0.1 /* dim_threshold */);
-
-  SmartDimModelImpl smart_dim_model;
-  if (UsesMlService())
-    InjectFakeMlServiceClient(&smart_dim_model);
+  InjectFakeMlServiceClient(&smart_dim_model);
 
   bool callback_done = false;
   smart_dim_model.RequestDimDecision(
@@ -198,8 +154,10 @@
                                EXPECT_EQ(
                                    UserActivityEvent::ModelPrediction::NO_DIM,
                                    prediction.response());
-                               EXPECT_EQ(47, prediction.decision_threshold());
-                               EXPECT_EQ(2, prediction.inactivity_score());
+                               EXPECT_EQ(kQuantizedHighDimThreshold,
+                                         prediction.decision_threshold());
+                               EXPECT_EQ(kQuantizedTestInactivityScore,
+                                         prediction.inactivity_score());
                                *callback_done = true;
                              },
                              &callback_done));
@@ -207,13 +165,13 @@
   EXPECT_TRUE(callback_done);
 }
 
-TEST_P(SmartDimModelImplTest, ShouldDim) {
+// With a low dim threshold, DIM decision is expected.
+TEST_F(SmartDimModelImplTest, ShouldDim) {
   SmartDimFeatureFlags flags;
-  flags.Initialize(UsesMlService(), -10.0 /* dim_threshold */);
+  flags.Initialize(kLowDimThreshold);
 
   SmartDimModelImpl smart_dim_model;
-  if (UsesMlService())
-    InjectFakeMlServiceClient(&smart_dim_model);
+  InjectFakeMlServiceClient(&smart_dim_model);
 
   bool callback_done = false;
   smart_dim_model.RequestDimDecision(
@@ -223,8 +181,10 @@
                                EXPECT_EQ(
                                    UserActivityEvent::ModelPrediction::DIM,
                                    prediction.response());
-                               EXPECT_EQ(0, prediction.decision_threshold());
-                               EXPECT_EQ(2, prediction.inactivity_score());
+                               EXPECT_EQ(kQuantizedLowDimThreshold,
+                                         prediction.decision_threshold());
+                               EXPECT_EQ(kQuantizedTestInactivityScore,
+                                         prediction.inactivity_score());
                                *callback_done = true;
                              },
                              &callback_done));
@@ -234,13 +194,12 @@
 
 // Check that CancelableCallback ensures a callback doesn't execute twice, in
 // case two RequestDimDecision() calls were made before any callback ran.
-TEST_P(SmartDimModelImplTest, CheckCancelableCallback) {
+TEST_F(SmartDimModelImplTest, CheckCancelableCallback) {
   SmartDimFeatureFlags flags;
-  flags.Initialize(UsesMlService(), -10.0 /* dim_threshold */);
+  flags.Initialize(kLowDimThreshold);
 
   SmartDimModelImpl smart_dim_model;
-  if (UsesMlService())
-    InjectFakeMlServiceClient(&smart_dim_model);
+  InjectFakeMlServiceClient(&smart_dim_model);
 
   bool callback_done = false;
   int num_callbacks_run = 0;
@@ -252,8 +211,10 @@
                UserActivityEvent::ModelPrediction prediction) {
               EXPECT_EQ(UserActivityEvent::ModelPrediction::DIM,
                         prediction.response());
-              EXPECT_EQ(0, prediction.decision_threshold());
-              EXPECT_EQ(2, prediction.inactivity_score());
+              EXPECT_EQ(kQuantizedLowDimThreshold,
+                        prediction.decision_threshold());
+              EXPECT_EQ(kQuantizedTestInactivityScore,
+                        prediction.inactivity_score());
               *callback_done = true;
               (*num_callbacks_run)++;
             },
@@ -266,13 +227,12 @@
 
 // Check that CancelPreviousRequest() can successfully prevent a previous
 // requested dim decision request from running.
-TEST_P(SmartDimModelImplTest, CheckCanceledRequest) {
+TEST_F(SmartDimModelImplTest, CheckCanceledRequest) {
   SmartDimFeatureFlags flags;
-  flags.Initialize(UsesMlService(), -10.0 /* dim_threshold */);
+  flags.Initialize(kLowDimThreshold);
 
   SmartDimModelImpl smart_dim_model;
-  if (UsesMlService())
-    InjectFakeMlServiceClient(&smart_dim_model);
+  InjectFakeMlServiceClient(&smart_dim_model);
 
   bool callback_done = false;
   smart_dim_model.RequestDimDecision(
@@ -287,10 +247,6 @@
   EXPECT_FALSE(callback_done);
 }
 
-INSTANTIATE_TEST_SUITE_P(SmartDimModelImplTests,
-                         SmartDimModelImplTest,
-                         testing::Bool());
-
 }  // namespace ml
 }  // namespace power
 }  // namespace chromeos
diff --git a/chrome/browser/chromeos/power/ml/smart_dim/tf_native_inference.cc b/chrome/browser/chromeos/power/ml/smart_dim/tf_native_inference.cc
deleted file mode 100644
index ddbd8035..0000000
--- a/chrome/browser/chromeos/power/ml/smart_dim/tf_native_inference.cc
+++ /dev/null
@@ -1,3061 +0,0 @@
-// Copyright 2018 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 file was generated using tf.native from a neural network trained by
-// TensorFlow, then simplified and cleaned up by hand. Please do not edit except
-// when updating to a new model.
-
-#include "chrome/browser/chromeos/power/ml/smart_dim/tf_native_inference.h"
-
-#include <algorithm>
-#include <cmath>
-#include <limits>
-
-#include "base/logging.h"
-
-namespace chromeos {
-namespace power {
-namespace ml {
-namespace tfnative_model {
-namespace {
-
-// The size of a shape in terms of number of coefficients.
-inline int32_t ShapeSize(const int32_t rank, const int32_t* shape) {
-  int32_t size = 1;
-  for (int32_t i = 0; i < rank; ++i)
-    size *= shape[i];
-  return size;
-}
-
-template <typename T>
-void FullyConnected(const int32_t* __restrict input_shape,
-                    const T* __restrict input_values,
-                    const int32_t* __restrict weight_shape,
-                    const T* __restrict weight_values,
-                    const int32_t* __restrict bias_shape,
-                    const T* __restrict bias_values,
-                    T* __restrict output_values) {
-  const int32_t batch_size = input_shape[0];
-  const int32_t num_inputs = weight_shape[0];
-  const int32_t num_outputs = weight_shape[1];
-  CHECK_EQ(input_shape[1], num_inputs);
-  CHECK_EQ(bias_shape[0], num_outputs);
-  for (int32_t batch = 0; batch < batch_size; ++batch) {
-    for (int32_t out_i = 0; out_i < num_outputs; ++out_i) {
-      T value = 0;
-      for (int32_t in_i = 0; in_i < num_inputs; ++in_i) {
-        value += input_values[batch * num_inputs + in_i] *
-                 weight_values[in_i * num_outputs + out_i];
-      }
-      value += bias_values[out_i];
-      output_values[batch * num_outputs + out_i] = value;
-    }
-  }
-}
-
-// -----------------------------------------------------------------------------
-// Simple unary ops
-// -----------------------------------------------------------------------------
-
-template <typename T>
-void Relu(const int32_t rank,
-          const int32_t* __restrict input_shape,
-          const T* __restrict input_values,
-          T* __restrict output_values) {
-  const int32_t size = ShapeSize(rank, input_shape);
-  for (int32_t i = 0; i < size; ++i) {
-    const T value = input_values[i];
-    output_values[i] = std::max(value, static_cast<T>(0));
-  }
-}
-
-// -----------------------------------------------------------------------------
-// Dequantize ops
-// -----------------------------------------------------------------------------
-
-template <typename T>
-void DequantizeMinFirst(const int32_t rank,
-                        const int32_t* __restrict input_shape,
-                        const T* __restrict input_values,
-                        const float* __restrict min_range,
-                        const float* __restrict max_range,
-                        float* __restrict output_values) {
-  const int32_t size = ShapeSize(rank, input_shape);
-  const float range_scale = (max_range[0] - min_range[0]) /
-                            (static_cast<float>(std::numeric_limits<T>::max()) -
-                             std::numeric_limits<T>::min());
-  const float range_min_rounded =
-      (max_range[0] == min_range[0]
-           ? min_range[0]
-           : round(min_range[0] / range_scale) * range_scale);
-  for (int32_t i = 0; i < size; i++) {
-    output_values[i] = ((static_cast<int32_t>(input_values[i]) -
-                         std::numeric_limits<T>::min()) *
-                        range_scale) +
-                       range_min_rounded;
-  }
-}
-
-// -----------------------------------------------------------------------------
-// CONSTANTS
-// Note that for now, endianness of the target machine needs to match that of
-// the one training was performed on.
-// -----------------------------------------------------------------------------
-const int32_t dnn_logits_biases__2__cf__2_shape[1] = {1};
-const union {
-  uint8_t bytes[4];
-  float values[1];
-} dnn_logits_biases__2__cf__2 = {{
-    0xde, 0x82, 0x1e, 0x3d,
-}};
-
-const int32_t dnn_hiddenlayer_0_weights__1__cf__1_quantized_const_shape[2] = {
-    FEATURES_SIZE, DNN_BIASES_SIZE};
-const union {
-  uint8_t bytes[DNN_WEIGHTS_SIZE];
-  uint8_t values[DNN_WEIGHTS_SIZE];
-} dnn_hiddenlayer_0_weights__1__cf__1_quantized_const = {{
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-
-const union {
-  uint8_t bytes[4];
-  float values[1];
-} dnn_hiddenlayer_0_weights__1__cf__1_quantized_min = {{
-    0x77, 0xe6, 0x47, 0xc1,
-}};
-
-const int32_t dnn_logits_weights__3__cf__3_shape[2] = {DNN_BIASES_SIZE, 1};
-const union {
-  uint8_t bytes[2 * 2 * DNN_BIASES_SIZE];
-  float values[DNN_BIASES_SIZE];
-} dnn_logits_weights__3__cf__3 = {{
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-}};
-
-const union {
-  uint8_t bytes[4];
-  float values[1];
-} dnn_hiddenlayer_0_weights__1__cf__1_quantized_max = {{
-    0x33, 0x8b, 0x75, 0x41,
-}};
-
-const int32_t dnn_hiddenlayer_0_biases__0__cf__0_shape[1] = {DNN_BIASES_SIZE};
-const union {
-  uint8_t bytes[2 * 2 * DNN_BIASES_SIZE];
-  float values[DNN_BIASES_SIZE];
-} dnn_hiddenlayer_0_biases__0__cf__0 = {{
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-    0x4e, 0x99, 0x64, 0xbf, 0x7f, 0xfc, 0xe6, 0xbe, 0x11, 0xed, 0x3b, 0xbf,
-    0x50, 0xf0, 0x34, 0xbf, 0xcd, 0xbc, 0xbb, 0xbf, 0x80, 0xdb, 0x73, 0xbf,
-    0x82, 0x41, 0x3d, 0xbf, 0xee, 0xd3, 0x8c, 0xbf, 0xa1, 0x42, 0x28, 0xbf,
-    0x34, 0xb4, 0x87, 0xbf, 0x70, 0x7e, 0x51, 0xbf, 0x55, 0xce, 0x08, 0xbf,
-    0x2e, 0xf1, 0x9b, 0xbf, 0x8e, 0xc4, 0xa3, 0xbe, 0x13, 0x63, 0x39, 0xbf,
-    0xbf, 0x11, 0x41, 0xbf, 0xdb, 0xc7, 0xe1, 0xbf, 0x4e, 0x84, 0x31, 0xbf,
-    0xc9, 0xa0, 0x1f, 0xbf, 0xf4, 0x51, 0x4b, 0xbf, 0xf6, 0xb6, 0x21, 0xbf,
-    0x5a, 0x73, 0x4c, 0xbf, 0x14, 0xac, 0xb6, 0xbe, 0x9a, 0x26, 0x28, 0xbf,
-    0x8f, 0x03, 0xcf, 0xbe, 0x0a, 0x7c, 0x61, 0xbf, 0x4c, 0x6a, 0x52, 0xbf,
-    0x1c, 0x11, 0x3b, 0xbf, 0x5c, 0xe5, 0xbe, 0xbf, 0xb0, 0xfa, 0x76, 0xbf,
-    0xce, 0x1f, 0x5b, 0xbf, 0xe1, 0x69, 0x66, 0xbf, 0x34, 0x39, 0x51, 0xbf,
-    0xdb, 0xc0, 0x68, 0xbf, 0xca, 0x5a, 0x7d, 0xc0, 0x6a, 0xe3, 0x41, 0xbf,
-    0x30, 0x7b, 0x38, 0xbf, 0x7a, 0x50, 0x1d, 0xbf, 0x19, 0x17, 0xef, 0xbf,
-    0x30, 0xdc, 0xce, 0xbe, 0x67, 0x8e, 0xa7, 0xbf, 0x2e, 0x03, 0x35, 0xbf,
-    0xbb, 0x71, 0x89, 0xbe, 0x78, 0xae, 0xbb, 0xbe, 0xf3, 0xd1, 0x97, 0xbc,
-    0xf0, 0xbe, 0xc1, 0xbe, 0x92, 0x6d, 0x34, 0xbf, 0xde, 0xc5, 0xc3, 0xbe,
-    0xe2, 0x48, 0x30, 0xbf, 0x69, 0x13, 0x25, 0xbf, 0x91, 0xea, 0xb6, 0xbe,
-    0x35, 0xea, 0x11, 0xc0, 0x9d, 0xa5, 0xc5, 0xbf, 0xb5, 0xe4, 0x82, 0xbf,
-}};
-
-}  // anonymous namespace
-
-// -----------------------------------------------------------------------------
-// INFERENCE
-// -----------------------------------------------------------------------------
-
-void Inference(const float* __restrict features /* shape: 1,FEATURES_SIZE */
-               ,
-               float* __restrict prediction /* shape: 1,1 */
-               ,
-               FixedAllocations* __restrict fixed) {
-  const int32_t features_shape[] = {1, FEATURES_SIZE};
-
-  // dnn/hiddenlayer_0/weights/_1__cf__1
-  DequantizeMinFirst<uint8_t>(
-      2, dnn_hiddenlayer_0_weights__1__cf__1_quantized_const_shape,
-      dnn_hiddenlayer_0_weights__1__cf__1_quantized_const.values,
-      dnn_hiddenlayer_0_weights__1__cf__1_quantized_min.values,
-      dnn_hiddenlayer_0_weights__1__cf__1_quantized_max.values, fixed->alloc0);
-
-  fixed->alloc0_shape[0] = FEATURES_SIZE;
-  fixed->alloc0_shape[1] = DNN_BIASES_SIZE;
-
-  // dnn/hiddenlayer_0/MatMul_merged_with_dnn/hiddenlayer_0/BiasAdd
-  FullyConnected<float>(features_shape, features, fixed->alloc0_shape,
-                        fixed->alloc0, dnn_hiddenlayer_0_biases__0__cf__0_shape,
-                        dnn_hiddenlayer_0_biases__0__cf__0.values,
-                        fixed->alloc1);
-  fixed->alloc1_shape[0] = 1;
-  fixed->alloc1_shape[1] = DNN_BIASES_SIZE;
-
-  // dnn/hiddenlayer_0/hiddenlayer_0/Relu
-  Relu<float>(2,  // rank
-              fixed->alloc1_shape, fixed->alloc1, fixed->alloc0);
-  fixed->alloc0_shape[0] = 1;
-  fixed->alloc0_shape[1] = DNN_BIASES_SIZE;
-
-  // dnn/logits/MatMul_merged_with_dnn/logits/BiasAdd
-  FullyConnected<float>(
-      fixed->alloc0_shape, fixed->alloc0, dnn_logits_weights__3__cf__3_shape,
-      dnn_logits_weights__3__cf__3.values, dnn_logits_biases__2__cf__2_shape,
-      dnn_logits_biases__2__cf__2.values, prediction);
-}
-
-}  // namespace tfnative_model
-}  // namespace ml
-}  // namespace power
-}  // namespace chromeos
diff --git a/chrome/browser/chromeos/power/ml/smart_dim/tf_native_inference.h b/chrome/browser/chromeos/power/ml/smart_dim/tf_native_inference.h
deleted file mode 100644
index c7a6858..0000000
--- a/chrome/browser/chromeos/power/ml/smart_dim/tf_native_inference.h
+++ /dev/null
@@ -1,43 +0,0 @@
-// Copyright 2018 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 file was generated using tf.native from a neural network trained by
-// TensorFlow, then cleaned up by hand. Please do not edit except to update
-// the constants for a new model.
-
-#ifndef CHROME_BROWSER_CHROMEOS_POWER_ML_SMART_DIM_TF_NATIVE_INFERENCE_H_
-#define CHROME_BROWSER_CHROMEOS_POWER_ML_SMART_DIM_TF_NATIVE_INFERENCE_H_
-
-#include <cstdint>
-
-namespace chromeos {
-namespace power {
-namespace ml {
-namespace tfnative_model {
-
-constexpr int DNN_WEIGHTS_SIZE = 33900;
-constexpr int DNN_RANK = 2;
-constexpr int FEATURES_SIZE = 565;
-constexpr int DNN_BIASES_SIZE = 60;
-
-struct alignas(16) FixedAllocations {
-  float alloc0[DNN_WEIGHTS_SIZE];
-  int32_t alloc0_shape[DNN_RANK];
-  float alloc1[DNN_BIASES_SIZE];
-  int32_t alloc1_shape[DNN_RANK];
-};
-
-void Inference(
-    /* size: FEATURES_SIZE */
-    const float* __restrict features,
-    /* size: 1 */
-    float* __restrict prediction,
-    FixedAllocations* __restrict fixed);
-
-}  // namespace tfnative_model
-}  // namespace ml
-}  // namespace power
-}  // namespace chromeos
-
-#endif  // CHROME_BROWSER_CHROMEOS_POWER_ML_SMART_DIM_TF_NATIVE_INFERENCE_H_
diff --git a/chrome/browser/flag_descriptions.cc b/chrome/browser/flag_descriptions.cc
index a969fe2..33a044f 100644
--- a/chrome/browser/flag_descriptions.cc
+++ b/chrome/browser/flag_descriptions.cc
@@ -3177,11 +3177,6 @@
     " until Chrome OS is unlocked to protect against malicious USB devices."
     " Already connected USB devices will continue to function.";
 
-const char kUserActivityPredictionMlServiceName[] =
-    "ML Service Smart Dim model";
-const char kUserActivityPredictionMlServiceDescription[] =
-    "Uses the new ML Service model for user activity prediction (Smart Dim).";
-
 const char kVaapiJpegImageDecodeAccelerationName[] =
     "VA-API JPEG decode acceleration for images";
 const char kVaapiJpegImageDecodeAccelerationDescription[] =
diff --git a/chrome/browser/flag_descriptions.h b/chrome/browser/flag_descriptions.h
index 8a6fce6..0aca82c 100644
--- a/chrome/browser/flag_descriptions.h
+++ b/chrome/browser/flag_descriptions.h
@@ -1915,9 +1915,6 @@
 extern const char kUseMonitorColorSpaceName[];
 extern const char kUseMonitorColorSpaceDescription[];
 
-extern const char kUserActivityPredictionMlServiceName[];
-extern const char kUserActivityPredictionMlServiceDescription[];
-
 extern const char kVaapiJpegImageDecodeAccelerationName[];
 extern const char kVaapiJpegImageDecodeAccelerationDescription[];
 
diff --git a/chromeos/constants/chromeos_features.cc b/chromeos/constants/chromeos_features.cc
index b8aa208..ae129e4 100644
--- a/chromeos/constants/chromeos_features.cc
+++ b/chromeos/constants/chromeos_features.cc
@@ -124,11 +124,6 @@
 const base::Feature kUserActivityPrediction{"UserActivityPrediction",
                                             base::FEATURE_ENABLED_BY_DEFAULT};
 
-// Enables or disables ML service inferencing (instead of TFNative inferencing)
-// for the Smart Dim feature on Chrome OS.
-const base::Feature kUserActivityPredictionMlService{
-    "UserActivityPredictionMlService", base::FEATURE_ENABLED_BY_DEFAULT};
-
 // Enable or disable native controls in video player on Chrome OS.
 const base::Feature kVideoPlayerNativeControls{
     "VideoPlayerNativeControls", base::FEATURE_ENABLED_BY_DEFAULT};
diff --git a/chromeos/constants/chromeos_features.h b/chromeos/constants/chromeos_features.h
index 670eb75..d1987c2 100644
--- a/chromeos/constants/chromeos_features.h
+++ b/chromeos/constants/chromeos_features.h
@@ -62,8 +62,6 @@
 COMPONENT_EXPORT(CHROMEOS_CONSTANTS)
 extern const base::Feature kUserActivityPrediction;
 COMPONENT_EXPORT(CHROMEOS_CONSTANTS)
-extern const base::Feature kUserActivityPredictionMlService;
-COMPONENT_EXPORT(CHROMEOS_CONSTANTS)
 extern const base::Feature kVideoPlayerNativeControls;
 
 // Keep alphabetized.