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Refactor(JAX): Use jax.jit's out_shardings instead of _enforce_jax_state_sharding #21559

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This is a refactor of the JAX trainer's sharding logic to simplify the code.

The logic previously handled by _enforce_jax_state_sharding has been moved into make_train_function, make_test_function, and make_predict_function. This is the ideal location, as it's where we call jax.jit. The now-redundant _enforce_jax_state_sharding method has been removed.

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Summary of Changes

Hello @buildwithsuhana, 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!

I've refactored the JAX trainer's sharding logic to streamline the code. This change moves the responsibility of enforcing JAX state sharding directly into the make_train_function, make_test_function, and make_predict_function methods, where jax.jit is invoked. By doing so, I've eliminated the need for the _enforce_jax_state_sharding method, making the sharding process more integrated and efficient. This refactor simplifies the overall architecture and improves how sharding is handled within the JAX backend.

Highlights

  • Code simplification: The internal method _enforce_jax_state_sharding has been removed, simplifying the codebase.
  • Improved sharding integration: The sharding logic is now directly integrated into make_train_function, make_test_function, and make_predict_function by utilizing the out_shardings argument of jax.jit.
  • New test coverage: A new test case, JAXTrainerShardingTest, has been added to validate the updated sharding behavior within the JAX trainer.
  • Refactored JAX sharding: The JAX trainer's sharding mechanism has been refactored to leverage jax.jit's out_shardings argument, replacing the previous _enforce_jax_state_sharding method.
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Code Review

This pull request refactors the JAX trainer's sharding logic by replacing the _enforce_jax_state_sharding method with the out_shardings argument of jax.jit. This is a good simplification of the codebase. My review includes a suggestion to further refactor the new logic to reduce code duplication and a minor style fix in the new test file. Overall, the changes look good and are well-tested.

buildwithsuhana and others added 2 commits August 8, 2025 10:49
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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Thanks for the PR!

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codecov-commenter commented Aug 11, 2025

Codecov Report

❌ Patch coverage is 55.55556% with 8 lines in your changes missing coverage. Please review.
✅ Project coverage is 82.72%. Comparing base (6114a21) to head (d534ec3).
⚠️ Report is 11 commits behind head on master.

Files with missing lines Patch % Lines
keras/src/backend/jax/trainer.py 55.55% 6 Missing and 2 partials ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##           master   #21559      +/-   ##
==========================================
- Coverage   82.73%   82.72%   -0.01%     
==========================================
  Files         567      567              
  Lines       56456    56454       -2     
  Branches     8823     8816       -7     
==========================================
- Hits        46710    46704       -6     
- Misses       7582     7587       +5     
+ Partials     2164     2163       -1     
Flag Coverage Δ
keras 82.53% <55.55%> (-0.01%) ⬇️
keras-jax 63.75% <55.55%> (-0.07%) ⬇️
keras-numpy 58.39% <0.00%> (+0.09%) ⬆️
keras-openvino 34.68% <0.00%> (+0.04%) ⬆️
keras-tensorflow 64.32% <0.00%> (+0.07%) ⬆️
keras-torch 63.93% <0.00%> (+0.06%) ⬆️

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train_step = jit(self.train_step, donate_argnums=0)
out_shardings = None
if distribution_lib.distribution() is not None:
state_shardings = self._record_training_state_sharding_spec()
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self._record_training_state_sharding_spec() does not return anything (and therefore returns None). So you're setting out_shardings to (None, None).

You do want to:

  • rename _record_training_state_sharding_spec to something like _get_state_sharding_spec
  • have it not set self. attributes
  • have it return the shardings instead

The worrying part is that no unit test failed. Can we have a unit test that fails when the shardings are not set correctly?

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