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Bump keras from 3.12.3 to 3.15.0 in /sdks/python/container/ml/py310 - #39687

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Bump keras from 3.12.3 to 3.15.0 in /sdks/python/container/ml/py310#39687
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Bumps keras from 3.12.3 to 3.15.0.

Release notes

Sourced from keras's releases.

v3.15.0

Highlights

  • Keras-to-Torch Export: New export_torch enables exporting Keras models to native PyTorch nn.Module format, along with LiteRT (TFLite) export support for the PyTorch backend.
  • Sliding Window Attention: Added sliding_window parameter to MultiHeadAttention and GroupedQueryAttention for efficient long-context attention.
  • Flash / Fused SDPA: Causal-only MHA/GQA now automatically dispatches to Flash Attention (cuDNN SDPA), and the manual attention path correctly applies causal masking.
  • Multi-Optimizer Training: New MultiOptimizer supports assigning different optimizers to sub-networks.
  • New Math Operations: Added unique, pinv, matrix_rank, fabs, fmax, fmin, erfc, dsplit, percentile, nanpercentile, sobel_edges, and ssim (structural similarity) to keras.ops.
  • Security Hardening: Comprehensive hardening of model reloading against HDF5 exploits, tar/zip traversal attacks, insecure deserialization.

New Features and Operations

Multi-Backend Operations

  • New NumPy Operations: Added unique, fabs, fmax, fmin, dsplit, erfc, percentile, nanpercentile in keras.ops.numpy.
  • New Linear Algebra Operations: Added pinv (pseudo-inverse) and matrix_rank in keras.ops.linalg.
  • New Image Operations: Added sobel_edges for edge detection and ssim (structural similarity) in keras.ops.image.
  • Negative Axes in Transpose: keras.ops.transpose now supports negative axis values.

Layers and Attention

  • Sliding Window Attention: MultiHeadAttention and GroupedQueryAttention layers support the sliding_window parameter for efficient long-sequence processing.
  • Flash Attention Engagement: Causal-only attention in MHA/GQA now uses Flash SDPA for significant speedups.
  • Fused Bidirectional LSTM/GRU: JAX backend now fuses Bidirectional LSTM into a single cuDNN call; fused bidirectional GRU added for Torch backend.
  • CTC Beam Search Decoder: Added CTC beam search decoding for the Torch backend.

Training and Optimizers

  • MultiOptimizer: Supports training sub-networks with different optimizers.
  • SKLearn Classifier: Added predict_proba method to SKLearnClassifier.

Export and Deployment

  • Keras-to-Torch Export: Export Keras models to native PyTorch nn.Module via model.export(..., format="torch").
  • LiteRT (TFLite) Export for PyTorch: Added LiteRT export support for models using the PyTorch backend.
  • LiteRT Compatibility Fix: Fixed LiteRT export for Keras 3 + TF 2.20 + Python 3.13.
  • ONNX Export: Support for dict/list inputs in Torch ONNX export; documented static input signature requirement for LiteRT PyTorch export.

Distribution and Parallelism

  • ModelParallel Improvements: Defined contiguous replica-group data shard ID convention; added distribution information (num_processes, num_model_replicas, data_shard_id).
  • Initializer Distribution Layout: Initializers can now handle the distribution layout directly with JAX.
  • TF Dataset Distribution: Refactored TF dataset distribution with centralized sharding routing; fixed data distribution for model training in JAX.

OpenVINO Backend Support

... (truncated)

Commits
  • 9d1bbf9 Add erfinv tests and TensorFlow CPU fallback for half precision (#23086)
  • b34af30 Fix pad_sequences string dtype check (np.bytes_ instead of duplicate np.str_)...
  • f512e93 Fix wrong parameter names in ops.select and ops.argpartition docstrings (#23091)
  • 915ec7e Support native Grouped-Query Attention (GQA) Key/Value head broadcast. (#23081)
  • 49d668d Add JAX multi-process distribution tests (#23105)
  • b49fde7 Refactor rematerialization logic into Operation and support more modes (#23107)
  • e0bfa2d Add to the list of APIs that should not be part of a reloaded model. (#23115)
  • 69d7fd6 Suppress spurious 'Skipping nested container' warning on freshly-saved files ...
  • 048d142 Delete temp files after loading model from remote path. (#23113)
  • 46f5eac Bump GitHub Actions versions to the latest (#23104)
  • Additional commits viewable in compare view

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Bumps [keras](https://github.com/keras-team/keras) from 3.12.3 to 3.15.0.
- [Release notes](https://github.com/keras-team/keras/releases)
- [Commits](keras-team/keras@v3.12.3...v3.15.0)

---
updated-dependencies:
- dependency-name: keras
  dependency-version: 3.15.0
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python labels Aug 9, 2026
@github-actions github-actions Bot added the docker label Aug 9, 2026
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github-actions Bot commented Aug 9, 2026

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Closing this PR because dependabot updates for container/** are not allowed due to generated files and excluded_paths is disabled due to dependabot/dependabot-core#14408. Once issue is resolved, please remove this step.

@github-actions github-actions Bot closed this Aug 9, 2026
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OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version. You can also ignore all major, minor, or patch releases for a dependency by adding an ignore condition with the desired update_types to your config file.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.

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dependabot Bot deleted the dependabot/pip/sdks/python/container/ml/py310/keras-3.15.0 branch August 9, 2026 12:12
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