[OpenVINO backend] add __array__ method for OpenVINOKerasTenor

[Mohamed-Ashraf273]

@rkazants
@fchollet
In https://github.com/keras-team/keras-hub/blob/master/keras_hub/src/layers/preprocessing/masked_lm_mask_generator_test.py#L46-L59

This test and many other tests need this method to run

[codecov-commenter]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 82.75%. Comparing base (be9b002) to head (1b90447).
Report is 18 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #21458      +/-   ##
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+ Coverage   82.72%   82.75%   +0.02%     
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  Files         565      565              
  Lines       55219    55350     +131     
  Branches     8608     8635      +27     
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+ Hits        45682    45805     +123     
- Misses       7427     7443      +16     
+ Partials     2110     2102       -8     

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keras	82.56% <100.00%> (+0.02%)	⬆️
keras-jax	63.32% <0.00%> (-0.01%)	⬇️
keras-numpy	58.54% <0.00%> (+0.01%)	⬆️
keras-openvino	33.77% <100.00%> (-0.03%)	⬇️
keras-tensorflow	63.76% <0.00%> (+0.01%)	⬆️
keras-torch	63.37% <0.00%> (-0.01%)	⬇️

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[divyashreepathihalli]

/gemini review

[gemini-code-assist]

Code Review

This pull request adds the __array__ method to OpenVINOKerasTensor to improve compatibility with NumPy. A suggestion has been made to handle scalar tensors more efficiently.

[gemini-code-assist]

The current implementation checks if self.data is a numpy.ndarray. However, when convert_to_tensor is called with a scalar, self.data is set to that scalar value, and the check isinstance(self.data, np.ndarray) will be False. This results in calling convert_to_numpy(self), which compiles and runs an OpenVINO model to retrieve a scalar value that is already available. Consider optimizing for scalar types as well by checking if self.data is not None and then using np.asarray(self.data).

Suggested change

	def __array__(self):
	if self.data is not None and isinstance(self.data, np.ndarray):
	return self.data
	return convert_to_numpy(self)
	def __array__(self):
	if self.data is not None:
	return np.asarray(self.data)
	return convert_to_numpy(self)