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chromium / chromiumos / platform / tflite / refs/heads/stabilize-16433.43.B
commit683bdd4de3f18ed32cf32d4744683676c4ca3479[log] [tgz]
authorTommy Chiang <[email protected]>Wed Sep 10 02:36:17 2025
committerChromeos LUCI <[email protected]>Wed Sep 10 09:43:39 2025
treec8bf9b56bc09c18a64d16d44ab551fbea3454a33
parent3e165401461010a9e9381bccf0e71691d63edc8b [diff]
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, new/delete cannot handle properly.

Thus, use `OwnedNativeHandle` defined in `android/native_handle_util`
and manually malloc the memory to solve the issue.

BUG=b:443074562
TEST=CQ

Change-Id: I06e533441072e0945b4bb050e6b32dd2f8613691
Reviewed-on: https://chromium-review.googlesource.com/c/chromiumos/platform/tflite/+/6934338
Tested-by: Tommy Chiang <[email protected]>
Commit-Queue: Shik Chen <[email protected]>
Reviewed-by: Shik Chen <[email protected]>
Commit-Queue: Tommy Chiang <[email protected]>
Auto-Submit: Tommy Chiang <[email protected]>
2 files changed
tree: c8bf9b56bc09c18a64d16d44ab551fbea3454a33
  1. android/
  2. common/
  3. delegate/
  4. patch/
  5. script/
  6. tool/
  7. udev/
  8. .bazelignore
  9. .bazelrc
  10. .bazelversion
  11. .clang-format
  12. .gitignore
  13. BUILD.bazel
  14. CPPLINT.cfg
  15. DIR_METADATA
  16. OWNERS
  17. PRESUBMIT.cfg
  18. README.md
  19. WORKSPACE.bazel
README.md

ChromeOS TFLite

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

TensorFlow Patch Management

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:

  1. 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/.

  2. 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.

  3. 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.