Forward-fix for JAX API changes

[jakevdp]

In jax-ml/jax#33984, JAX will begin returning tuples rather than lists for several jax.numpy APIs. This fixes a breakage associated with that change.

[gemini-code-assist]

Summary of Changes

Hello @jakevdp, 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 an anticipated breaking change in the JAX library, specifically concerning the return type of certain jax.numpy functions. By proactively modifying the Keras JAX backend, it ensures that existing code remains functional and compatible when JAX transitions from returning lists to tuples for specific API calls, thereby safeguarding the stability of the Keras integration with JAX.

Highlights

• JAX API Compatibility: This pull request introduces a forward-fix to maintain compatibility with an upcoming JAX API change where several jax.numpy APIs will begin returning tuples instead of lists.
• Explicit List Conversion: The one_hot function within the Keras JAX backend has been updated to explicitly convert the output of jnp.meshgrid to a list, preventing potential breakage from the aforementioned JAX change.

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[gemini-code-assist]

Code Review

This pull request provides a forward-fix for an upcoming API change in JAX, where jnp.meshgrid will start returning a tuple instead of a list. The change correctly wraps the jnp.meshgrid call in list() within the one_hot function. This ensures compatibility with the subsequent .insert() call, which requires a list. The fix is correct and necessary. As a broader point of feedback, the keras.ops.meshgrid wrapper in keras/src/backend/jax/numpy.py is not updated in this PR. With the new JAX version, it will start returning a tuple, which is inconsistent with numpy.meshgrid's behavior of returning a list. It would be beneficial to also update the wrapper to return a list to maintain API consistency and prevent similar issues elsewhere. This aligns with the Keras API design guideline of maintaining consistency with NumPy conventions.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 82.67%. Comparing base (7edb6a4) to head (588d9dd).

Additional details and impacted files

@@           Coverage Diff           @@
##           master   #21938   +/-   ##
=======================================
  Coverage   82.67%   82.67%           
=======================================
  Files         588      588           
  Lines       61250    61250           
  Branches     9602     9602           
=======================================
  Hits        50637    50637           
  Misses       8129     8129           
  Partials     2484     2484           

Flag	Coverage Δ
keras	82.49% <100.00%> (ø)
keras-jax	61.69% <100.00%> (ø)
keras-numpy	56.93% <0.00%> (ø)
keras-openvino	37.21% <0.00%> (ø)
keras-tensorflow	63.86% <0.00%> (ø)
keras-torch	62.60% <0.00%> (ø)

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