Implement complete Keras-Orbax checkpoint integration by amitsrivastava78 · Pull Request #22002 · keras-team/keras (original) (raw)

• Add compile config saving to OrbaxCheckpoint for full model restoration
• Update saving_api.py to use compile_from_config for proper model loading
• Replace direct Orbax API tests with Keras saving API tests
• Remove unused Orbax imports from test file
• Add comprehensive test coverage for all model state components
• Ensure cross-backend compatibility (TensorFlow, JAX, PyTorch)

This enables users to save and load complete model state (weights, optimizer, metrics) using keras.saving.load_model() with Orbax checkpoints.

[](/apps/gemini-code-assist)

• Accept upstream changes for various backend and layer updates
• Re-apply Orbax checkpoint modifications
• Add comprehensive model state restoration test with JAX compatibility
• Ensure cross-backend compatibility for checkpoint loading

• Fix metrics initialization during model loading to ensure all metric variables are created before state restoration
• Add evaluation step during loading to initialize missing metrics like mean_absolute_error
• Update tests to verify exact metric value matching instead of just structure validation
• Fix async save exact weight matching using final checkpoint strategy
• Simplify JAX backend code by removing unnecessary numpy conversions
• Ensure compatibility across JAX, PyTorch, and TensorFlow backends
• All tests now pass with exact metrics comparison for proper checkpoint fidelity
• Fix line length compliance to stay within 80 columns

• Implement proper exact weight matching for async saves by forcing final sync checkpoint in on_train_end with max_to_keep=1
• Remove inappropriate epoch-based sync forcing that hurt performance
• Simplify weight getter API: remove redundant get_final_saved_weights and get_last_saved_weights_exact functions
• Fix line length compliance to stay under 80 columns
• All tests pass with exact weight matching for both sync and async saves

• Remove redundant numpy import (already imported at top)
• Use backend-aware state handling: JAX preserves native arrays, other backends convert to numpy for exact matching
• Simplify state copying logic using tree.map_structure
• Maintain 80-column line length compliance
• Preserve performance for JAX while ensuring exact matching works
• All tests pass across backends

• Consolidated 7 redundant tests into 3 optimized comprehensive tests
• Reduced test file size by 34% (1174 -> 817 lines) while maintaining coverage
• Fixed nested dictionary comparison for JAX optimizer state variables
• Enhanced cross-backend compatibility with graceful error handling
• Ensured all lines comply with 80-column limit for better readability
• All tests pass across JAX, TensorFlow, and PyTorch backends

Tests consolidated:

• test_checkpoint_loading_via_saving_api: Basic loading + weights-only error handling
• test_checkpoint_loading_full_state_via_saving_api: Optimizer/metrics state loading
• test_comprehensive_model_state_restoration: Advanced state restoration with custom layers
• test_exact_weight_matching_with_sync_save: Sync vs async weight matching verification

Performance improvements:

• Use os.scandir() for 2-3x faster step detection vs file_utils calls
• Consolidate imports to reduce repeated import overhead
• Streamline state tree preparation with dictionary comprehension

Code simplification:

• Simplified model building and compilation logic
• Reduced nested conditions for better readability
• Optimized metrics initialization with cleaner logic
• Enhanced error handling without losing functionality

Results:

• 30-line reduction (521 → 493 lines) - 6% file size reduction
• Improved performance with faster directory operations
• Maintained cross-backend compatibility (JAX, TensorFlow, PyTorch)
• All lines comply with 80-column limit
• All tests passing with optimized implementation

Problem:

• test_save_on_background_async failing with 'Too many open files' error
• Manual orbax checkpoint detection in load_model() caused fd leaks
• Redundant code duplicated checkpoint detection logic

Solution:

• Replace manual detection with imported is_orbax_checkpoint() utility
• Eliminate file_utils.listdir() calls that leaked file descriptors
• Use existing optimized checkpoint detection logic

Results:

• Fixed OSError: [Errno 24] Too many open files in async tests
• Removed code duplication and improved maintainability
• All orbax checkpoint tests now passing consistently
• Better performance with optimized checkpoint detection

Problem:

• 'Too many open files' errors in async/sync checkpoint tests
• Orbax checkpointer file descriptors not properly cleaned up
• Tests failing in CI environment due to accumulated open file handles

Solution:

• Added del method to OrbaxCheckpoint for automatic cleanup
• Added try/finally blocks in tests for explicit cleanup
• Ensures checkpointer.close() is called in all scenarios

Root Cause Analysis:

• Orbax checkpointer maintains file descriptors for checkpoint operations
• Without proper cleanup via checkpointer.close(), these accumulate
• In test environments with multiple runs, this hits system limits

Fixes:

1. Automatic cleanup: del ensures cleanup during garbage collection
2. Explicit cleanup: try/finally blocks in async/sync tests
3. Defense in depth: Both normal and abnormal termination scenarios covered

Results:

• Resolves OSError: [Errno 24] Too many open files
• All async/sync checkpoint tests now pass consistently
• Proper resource management prevents file descriptor accumulation

Test file descriptor leak fixes in OrbaxCheckpoint:

• Enhanced resource management with retry logic for RESOURCE_EXHAUSTED errors
• Added garbage collection and explicit cleanup in sync save operations
• Improved test cleanup patterns to prevent file descriptor accumulation

• Remove redundant numpy conversion in OrbaxCheckpoint._save_checkpoint since _get_state_tree already handles format conversion
• Add future tracking for async saves to avoid memory issues with buffer donation
• Remove unused _training_ending flag and defensive self.model check
• Simplify redundant conditional logic in on_train_end fallback
• Remove manual model building in saving_api.py since build_config handles it
• Remove backwards compatibility optimizer_config fallback
• Remove unnecessary cross-backend numpy conversion assuming same-backend save/load
• Remove hacky metrics initialization via dummy evaluation
• Clean up and optimize checkpoint loading flow

• Add save_decision_policy=FixedIntervalPolicy(1) to fix race condition with rapid async saves
• Remove unnecessary on_train_end workaround (no longer needed with save_decision_policy)
• Remove get_last_saved_weights() method (tests use model.get_weights() directly)
• All tests pass with the cleaner implementation

• Consolidate checkpoint step detection to use find_latest_orbax_checkpoint() utility
• Remove duplicate os.scandir logic in _load_model_from_orbax_checkpoint
• Simplify state_tree filtering to only include keys that exist in composite_state
• More maintainable and DRY code

The overwrite parameter was never used (always defaulted to False) and is unnecessary with our preservation policy and save_decision_policy handling checkpoint management automatically.

The force_sync parameter was never used (always defaulted to None) and added unnecessary complexity. Sync vs async behavior is already controlled by the save_on_background constructor parameter, making this override unnecessary.

Orbax's checkpointer.close() already waits for pending async operations to complete before closing (per its API contract). The explicit wait_until_finished() call was redundant and added in later commits unnecessarily.

Reverting to the simpler original pattern where close() handles the wait.

• Remove redundant wait_until_finished() calls from tests since on_train_end already waits
• Remove unnecessary try/finally cleanup blocks in tests
• Remove unused _last_checkpoint_path variable in callback
• Use saving_lib._serialize_model_as_json for model config serialization (consistency and proper object sharing)
• Use saving_lib._model_from_config for model loading (handles shared objects and compile_config)
• Replace np.testing.assert_array_almost_equal with self.assertAllClose for better cross-backend compatibility
• Consolidate tests using parameterized tests (batch/epoch freq, sync/async, save_best_only modes)
• Remove redundant test_directory_creation test
• All tests pass on JAX, PyTorch, and TensorFlow backends

…test structure

• Move imports to top of file (saving, utils, register_keras_serializable)
• Remove import keras statements, use specific imports instead
• Replace keras.utils and keras.backend with direct module usage
• Simplify optimizer variable comparison using direct iteration
• Remove complex nested state tree comparison, use simple weight/optimizer variable loops
• Parametrize test_comprehensive_model_state_restoration with sync/async modes
• Remove redundant test_exact_weight_matching_with_sync_save (covered by parametrized test)
• Remove redundant test_checkpoint_loading_full_state_via_saving_api (covered by comprehensive test)
• Simplify test logic leveraging assertAllClose's built-in numpy conversion

jerryxyj added a commit to jerryxyj/keras that referenced this pull request

Feb 14, 2026

• Implement logaddexp2 function in keras.ops (keras-team#21691)

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• Refactor variable serialization. (keras-team#21713)

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• Add eye support for OpenVINO backend (keras-team#21739)

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• Implement isreal function in keras.ops (keras-team#21740)

• Remove the unused jax enable_x64. (keras-team#21737)

• Correct implementation for several OpenVINO operations (keras-team#21746)

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• Fix discretization discrepancy (keras-team#21769)

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• Fix: keras.ops.quantile works with tf graph execution (keras-team#21782)

• Fix typo in Distiller docstring

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• Update Keras backend installation instructions

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• Fix tf dataset detection logic. (keras-team#21794)

• update test after jax.config.jax_vjp3 is enabled (keras-team#21776)

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• Add missing convert_to_tensor to take_along_axis on JAX. (keras-team#21825)

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• Bump the github-actions group with 4 updates (keras-team#21809)

• Fix typo in CONTRIBUTING.md (keras-team#21812)

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• Fix CosineDecay documentation to clarify alpha is a multiplier (keras-team#21827)

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• Fix typos in some files (keras-team#21830)

• Fix failing sklearn tests following release of pytest 9.0. (keras-team#21843)

• Implement empty_like function in keras.ops (keras-team#21840)

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• Fix typo in variable name 'embeding' to 'embedding' (keras-team#21845)

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• Fix assigning a value to a variable within an autocast scope. (keras-team#21864)

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• standardize_shape normalizes the dimensions and tuple. (keras-team#21867)

• Improve error message when layer/model input validation fails. (keras-team#21869)

• Add verbose logging when ModelCheckpoint callback is done saving ... …

• [OpenVINO backend] Remove deprecated openvino.runtime import (keras-team#21826)

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• Fix NNX tests (keras-team#21884)

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• fix tpu test (keras-team#21893)

• Model Export to liteRT (keras-team#21674)

• Fix: torch layer losses keyword arguments in rematscope (keras-team#21865)

• Add label to trigger TPU tests manually. (keras-team#21897)

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• remove log (keras-team#21901)

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• Update dependencies and dependabot.yml. (keras-team#21974)

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• Adds support for AWQ (keras-team#21992)

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• Fix typo and improve docstring formatting (keras-team#22017)

• Implement nansum function in keras.ops (keras-team#21996)

• Fix unreliable Orbax checkpoint detection with custom implementation …

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• Allow CenterCrop layer to handle dynamic image sizes. (keras-team#22020)

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• Refactor ExtractPatches to handle both 2D and 3D (keras-team#22013)

• Implement argpartition function for OpenVINO backend (keras-team#22025)

• Implement logaddexp2 function for OpenVINO backend (keras-team#22026)

• Implement nanmin function in keras.ops (keras-team#22040)

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• feat: Add documentation examples for image preprocessing augmentation…

• Fix: activity regularizer not normalized by batch size (keras-team#22021)

• Implement ldexp and select ops for OpenVINO backend (keras-team#22042)

• Fix: convert deque to list before tf.transpose in keras.ops.quantile …

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• Implement ptp function for OpenVINO backend (keras-team#22060)

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• Implement complete Keras-Orbax checkpoint integration (keras-team#22002)

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• Fix TrackedDict constructor to support iterable (key, value) inputs (…

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• [Keras 3] Refactor ExportArchive to be a dispatcher for different exp…

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