Fix test failures when nnx is enabled

[shashaka]

This PR fixes test failures when nnx is enabled in JAX backend.
train_step and test_step are wrapped using unbound methods with nnx.jit to make them compatible with NNX JIT.

[gemini-code-assist]

Summary of Changes

Hello @shashaka, 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 addresses and resolves test failures that occur in the JAX backend when the Neural Networks eXperiments (NNX) feature is active. The solution involves modifying the JIT compilation strategy for the train_step and test_step methods, ensuring they are compatible with NNX's JIT requirements by wrapping them as unbound methods.

Highlights

• NNX Compatibility for train_step: The train_step function is now conditionally wrapped with nnx.jit using an unbound method (type(self).train_step) when NNX is enabled, resolving test failures.
• NNX Compatibility for test_step: Similarly, the test_step function is also conditionally wrapped with nnx.jit using an unbound method (type(self).test_step) when NNX is enabled to ensure proper JIT compilation.

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[gemini-code-assist]

Code Review

This pull request addresses test failures when NNX is enabled in the JAX backend by wrapping train_step and test_step methods with a lambda function before JIT compilation. This is a good fix to ensure compatibility with NNX.

My review includes suggestions to refactor the new code in make_train_function and make_test_function to reduce code duplication. By selecting the appropriate step function before the jit call, we can make the code more concise and maintainable.

Overall, the changes are correct and necessary. Applying the suggested refactoring will further improve the code quality.

[codecov-commenter]

Codecov Report

❌ Patch coverage is 33.33333% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 82.57%. Comparing base (cc90ffd) to head (2c46fa4).
⚠️ Report is 1 commits behind head on master.

Files with missing lines	Patch %	Lines
keras/src/backend/jax/trainer.py	33.33%	2 Missing and 2 partials ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #21875      +/-   ##
==========================================
- Coverage   82.57%   82.57%   -0.01%     
==========================================
  Files         577      577              
  Lines       59593    59599       +6     
  Branches     9349     9351       +2     
==========================================
+ Hits        49211    49213       +2     
- Misses       7976     7978       +2     
- Partials     2406     2408       +2     

Flag	Coverage Δ
keras	82.39% <33.33%> (-0.01%)	⬇️
keras-jax	62.88% <33.33%> (-0.01%)	⬇️
keras-numpy	57.52% <0.00%> (-0.01%)	⬇️
keras-openvino	34.34% <0.00%> (-0.01%)	⬇️
keras-tensorflow	64.40% <0.00%> (-0.01%)	⬇️
keras-torch	63.57% <0.00%> (-0.01%)	⬇️

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[fchollet]

Thanks for the PR. How do we test this on CI?