tflite: Fix native handle deallocation size mismatch The default new/delete memory management will act based on the given type. However, since native_handle_t contains zero-length (dynamic size) array, which new/delete cannot handle properly. Thus, instead of relying on the default deleter in the unique_ptr, which use delete, this CL create a custom deleter that use malloc/free to match the C behavior, which makes memory size management easier. BUG=b:442765928 TEST=bazelisk test --config=host_clang '//android:hardware_buffer_test' Change-Id: I84364f4149a2da99742a40f201af3a17d9541d44 Reviewed-on: https://chromium-review.googlesource.com/c/chromiumos/platform/tflite/+/6908322 Auto-Submit: Tommy Chiang <ototot@google.com> Tested-by: Tommy Chiang <ototot@google.com> Reviewed-by: Shik Chen <shik@chromium.org> Commit-Queue: Shik Chen <shik@chromium.org>
This repository hosts the core ChromeOS TFLite components, enabling on-device machine learning (ODML) workloads accelerated by NPU.
The corresponding ebuild can be found at: tensorflow-9999.ebuild
Patches are stored in the patch/ directory and explicitly listed in WORKSPACE.bazel. A helper script, ./script/patcher.py, is included to facilitate patch management within a TFLite workspace.
The typical workflow:
Eject (Download) TensorFlow Source Code
Download the TensorFlow source code into a local git repository with patches applied as individual commits:
./script/patcher.py eject
This creates a new local git repository at tensorflow/.
Modify the TensorFlow Repository
Make changes to the tensorflow/ repository as needed, following standard git workflows. Optionally, include a PATCH_NAME= tag in commit messages to specify the filename of the corresponding patch.
Seal the Repository
Regenerate the patch files and update the WORKSPACE.bazel file:
./script/patcher.py seal
This updates the patches in the patch/ directory and reflects the changes in WORKSPACE.bazel.
It's preferred to submit changes to upstream TensorFlow first and cherry-pick them as patches. This helps minimize divergence and makes TensorFlow updates easier.