Do not always make batch size dynamic during export.

[hertschuh]

This is a follow-up of #21674

This PR changed the signature of make_tf_tensor_spec from (x) to (x, dynamic_batch=True), thereby adding the ability to make the batch size dynamic.

This PR also adds _get_save_spec(self, dynamic_batch=True) which uses make_tf_tensor_spec and forwards the dynamic_batch argument.

However, the default before this change for other export (SavedModel, ONNX) was to keep the batch size untouched. In particular, when a user manually provides an input_signature to ExportArchive.add_endpoint, we should honor it. The user controls whether the batch size is dynamic or not in the input_signature.

This PR changes the default of make_tf_tensor_spec back to dynamic_batch=False to revert SavedModel and ONNX exports to the previous behavior.

Also removed call to return super()._get_save_spec(dynamic_batch) which can never succeed as TFLayer is a top level class (ignoring the auto-tracking stuff).

[gemini-code-assist]

Summary of Changes

Hello @hertschuh, 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 unintended change introduced in a previous PR (21674) that inadvertently made batch sizes dynamic by default during model export. By reverting the default dynamic_batch parameter in make_tf_tensor_spec to False, it ensures that SavedModel and ONNX exports honor the user's explicit input_signature regarding batch dynamism, restoring the expected behavior. Additionally, it includes a minor code cleanup by removing an unnecessary super() call in the TFLayer's _get_save_spec method.

Highlights

• Batch Size Default: The default value for the dynamic_batch parameter in make_tf_tensor_spec has been reverted from True to False.
• Export Behavior Restoration: This change restores the previous behavior for SavedModel and ONNX exports, ensuring that batch sizes are not made dynamic by default unless explicitly specified by the user's input_signature.
• Code Cleanup: An unreachable super()._get_save_spec call within the _get_save_spec method of TFLayer has been removed, as TFLayer is a top-level class.

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[gemini-code-assist]

Code Review

This pull request introduces two beneficial changes. First, it simplifies the _get_save_spec method in keras/src/backend/tensorflow/layer.py by removing an unreachable super() call within a try-except block. This is a good cleanup that improves code clarity. Second, it changes the default value of dynamic_batch to False in make_tf_tensor_spec in keras/src/export/export_utils.py. This change is important as it reverts the model export behavior to not modify the batch size by default, thus respecting user-provided input_signature and fixing a recent regression. The changes are well-justified and improve the codebase.

[codecov-commenter]

Codecov Report

❌ Patch coverage is 16.66667% with 5 lines in your changes missing coverage. Please review.
✅ Project coverage is 82.67%. Comparing base (203b72c) to head (ba8c3dd).

Files with missing lines	Patch %	Lines
keras/src/backend/tensorflow/layer.py	0.00%	5 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #21944      +/-   ##
==========================================
- Coverage   82.67%   82.67%   -0.01%     
==========================================
  Files         588      588              
  Lines       61250    61247       -3     
  Branches     9602     9602              
==========================================
- Hits        50637    50634       -3     
  Misses       8129     8129              
  Partials     2484     2484              

Flag	Coverage Δ
keras	82.49% <16.66%> (-0.01%)	⬇️
keras-jax	61.69% <16.66%> (-0.01%)	⬇️
keras-numpy	56.93% <16.66%> (+<0.01%)	⬆️
keras-openvino	37.21% <16.66%> (+<0.01%)	⬆️
keras-tensorflow	63.86% <16.66%> (-0.01%)	⬇️
keras-torch	62.60% <16.66%> (+<0.01%)	⬆️

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