[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

Attention: Patch coverage is 50.00000% with 1 line in your changes missing coverage. Please review.

Project coverage is 82.81%. Comparing base (d55a767) to head (75647be).

Files with missing lines	Patch %	Lines
keras/src/backend/openvino/core.py	50.00%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #21458      +/-   ##
==========================================
- Coverage   82.81%   82.81%   -0.01%     
==========================================
  Files         565      565              
  Lines       55520    55522       +2     
  Branches     8664     8664              
==========================================
+ Hits        45977    45978       +1     
- Misses       7428     7429       +1     
  Partials     2115     2115              

Flag	Coverage Δ
keras	82.62% <50.00%> (-0.01%)	⬇️
keras-jax	63.38% <0.00%> (-0.01%)	⬇️
keras-numpy	58.58% <0.00%> (-0.01%)	⬇️
keras-openvino	33.99% <50.00%> (+<0.01%)	⬆️
keras-tensorflow	63.83% <0.00%> (-0.01%)	⬇️
keras-torch	63.50% <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)