Pass the shape when creating a tf.Variable.

[hertschuh]

The value passed can be an initializer and the calling of the initializer may be delayed. Passing the shape immediately when creating the Variable helps in some scenarios, for instance when UninitializedVariable instances are used.

Note that this also works when self._shape is None.

[gemini-code-assist]

Summary of Changes

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This pull request enhances the robustness of tf.Variable creation within the Keras TensorFlow backend by ensuring that the variable's shape is immediately available upon instantiation. This is particularly beneficial for handling delayed initializers and UninitializedVariable instances, leading to more predictable and stable variable management.

Highlights

• TensorFlow Variable Initialization: The tf.Variable constructor now explicitly receives the shape argument during initialization. This change addresses scenarios where the value provided might be an initializer whose execution is delayed, or when dealing with UninitializedVariable instances.

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[gemini-code-assist]

Code Review

This pull request updates the TensorFlow backend's Variable class to explicitly pass the shape when creating a tf.Variable. This is a good improvement as it helps with scenarios involving deferred initialization, such as with UninitializedVariable instances, by providing the shape information upfront. The implementation correctly handles cases where self._shape is None, relying on TensorFlow's default behavior to infer the shape from the initial value. The change is correct and beneficial.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 83.08%. Comparing base (88b3c08) to head (6c25c5f).
⚠️ Report is 2 commits behind head on master.

Additional details and impacted files

@@           Coverage Diff           @@
##           master   #22460   +/-   ##
=======================================
  Coverage   83.08%   83.08%           
=======================================
  Files         596      596           
  Lines       67337    67337           
  Branches    10491    10491           
=======================================
  Hits        55945    55945           
  Misses       8687     8687           
  Partials     2705     2705           

Flag	Coverage Δ
keras	82.91% <ø> (ø)
keras-jax	60.02% <ø> (ø)
keras-numpy	54.30% <ø> (ø)
keras-openvino	50.86% <ø> (ø)
keras-tensorflow	61.26% <ø> (+<0.01%)	⬆️
keras-torch	60.09% <ø> (ø)

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