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

[Junead04]

Summary
Fixed a ValueError in keras.ops.quantile when running under TensorFlow graph execution (@tf.function).
The issue was caused by passing a collections.deque object as the perm argument to tf.transpose.

Fix
Fixes #21781
Convert perm to a list before passing it to TensorFlow:
result = tf.transpose(result, perm=list(perm))

Test
Added a regression test verifying correct behavior under tf.function.
CC: @keras-team

[google-cla]

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[gemini-code-assist]

Summary of Changes

Hello @Junead04, 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 resolves a critical bug affecting the keras.ops.quantile function when used within TensorFlow's graph execution mode (@tf.function). The issue stemmed from an incompatibility between tf.transpose and collections.deque objects. The fix ensures proper operation by explicitly converting the permutation argument to a list, and a new test case has been introduced to prevent future regressions.

Highlights

• Bug Fix: Addresses a ValueError that occurred in keras.ops.quantile when executed within a TensorFlow graph (@tf.function).
• Root Cause: The error was caused by passing a collections.deque object as the perm argument to tf.transpose, which is not supported in TensorFlow's graph execution mode.
• Solution: The perm argument is now explicitly converted to a standard Python list before being passed to tf.transpose, resolving the compatibility issue.
• Testing: A new regression test, test_quantile_graph_mode, has been added to verify the correct behavior of keras.ops.quantile when running under tf.function.

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[gemini-code-assist]

Code Review

This pull request addresses a ValueError in keras.ops.quantile when used within a @tf.function in TensorFlow. The fix correctly converts a collections.deque object to a list before passing it to tf.transpose, which resolves the graph execution issue. A new regression test is also added to ensure this behavior is correct and prevent future regressions. The changes are accurate and well-tested. The pull request is well-structured and ready to be merged.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 79.38%. Comparing base (c2bc6cf) to head (8c02193).

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #21784      +/-   ##
==========================================
- Coverage   82.63%   79.38%   -3.26%     
==========================================
  Files         577      577              
  Lines       59316    59316              
  Branches     9300     9300              
==========================================
- Hits        49018    47087    -1931     
- Misses       7910     9944    +2034     
+ Partials     2388     2285     -103     

Flag	Coverage Δ
keras	79.21% <100.00%> (-3.25%)	⬇️
keras-jax	63.32% <0.00%> (ø)
keras-numpy	57.55% <0.00%> (ø)
keras-openvino	?
keras-tensorflow	64.11% <100.00%> (ø)
keras-torch	63.62% <0.00%> (ø)

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[keerthanakadiri]

Hi @Junead04, Can you please sign the CLA? Thank you!

[hertschuh]

Thanks for the fix!

[hertschuh]

This test already exists:

keras/keras/src/ops/numpy_test.py

Line 3347 in d662ac7

def test_quantile_in_tf_function(self):

Can you remove this file and modify the existing test to cover the case that was not working?

[hertschuh]

You'll also need to accept the CLA.

[Junead04]

Okk I will sign into the CLA.This is my first contribution so I don't know about this.Thank you for guiding me @keerthanakadiri @hertschuh