Remove completed TODO The patch management logic is moved here in crrev.com/c/5334638 BUG=b:314854484 TEST=none Change-Id: Iacb14a573b2774a4b0bad3fb66dbe6a6d4e898da Reviewed-on: https://chromium-review.googlesource.com/c/chromiumos/platform/tflite/+/7274900 Reviewed-by: Shik Chen <shik@chromium.org> Commit-Queue: Tommy Chiang <ototot@google.com> Auto-Submit: Tommy Chiang <ototot@google.com> Tested-by: Tommy Chiang <ototot@google.com>
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.