Orbax Loading and Sharding Support feature

[amitsrivastava78]

Support

1. New loading function for the orbax checkpointing
2. Support sharding feature

[gemini-code-assist]

Summary of Changes

Hello @amitsrivastava78, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances Keras's checkpoint loading capabilities by introducing a dedicated Model.load() method for Orbax checkpoints. This new functionality intelligently handles checkpoint directories, automatically identifying and loading the latest state. Crucially, it incorporates advanced sharding support for the JAX backend, allowing models to be loaded and resharded dynamically to match the current distribution configuration. Additionally, the Model.export() method has been refined by removing the LiteRT export option, focusing on core export functionalities.

Highlights

• New Model.load() method for Orbax Checkpoints: A new load method has been added to the Model class, enabling direct loading of Orbax checkpoints. This method can automatically detect the latest checkpoint in a directory or load a specific step.
• Sharding Support for JAX Backend: The Model.load() method now supports automatic resharding of data when loading Orbax checkpoints on the JAX backend, adapting to the current distribution strategy.
• Refined Model.export() Functionality: The Model.export() method has been updated to remove support for LiteRT export, streamlining the available export formats.
• Comprehensive Testing for Loading and Sharding: Extensive new tests have been added to orbax_checkpoint_test.py to validate the new Model.load() method, including synchronous/asynchronous saving, layout preservation, and JAX-specific resharding and distributed checkpoint structure verification.

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[gemini-code-assist]

Code Review

This pull request introduces significant new functionality for Orbax checkpoint loading and sharding support. The changes include a new Model.load() method, helper functions for checkpoint discovery, and a comprehensive suite of new tests. The implementation is generally solid and well-tested. My feedback focuses on improving code maintainability by reducing duplication and enhancing error handling in the new test cases.

[codecov-commenter]

Codecov Report

❌ Patch coverage is 56.97674% with 37 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.50%. Comparing base (f0a48a6) to head (c592a27).

Files with missing lines	Patch %	Lines
keras/src/callbacks/orbax_checkpoint.py	41.37%	14 Missing and 3 partials ⚠️
keras/src/models/model.py	64.51%	4 Missing and 7 partials ⚠️
keras/src/saving/saving_api.py	65.38%	4 Missing and 5 partials ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #21903      +/-   ##
==========================================
- Coverage   76.30%   71.50%   -4.80%     
==========================================
  Files         580      580              
  Lines       60029    60112      +83     
  Branches     9432     9450      +18     
==========================================
- Hits        45803    42982    -2821     
- Misses      11750    14759    +3009     
+ Partials     2476     2371     -105     

Flag	Coverage Δ
keras	71.40% <56.97%> (-4.77%)	⬇️
keras-jax	?
keras-numpy	57.26% <13.95%> (-0.06%)	⬇️
keras-openvino	34.27% <13.95%> (-0.03%)	⬇️
keras-torch	63.21% <56.97%> (-0.01%)	⬇️

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