[OpenVINO] Fix pad to accept float scalar constant_values

[goyaladitya05]

Description

The ov pad was rejecting any non-int constant_values with a ValueError, but float scalars (e.g. 0.0) are equally valid. This caused compute_quantization_parameters and abs_max_quantize_grouped_with_zero_point to fail when padding inputs whose dimension isn't divisible by block_size.

Widened the isinstance check from int to (int, float).
Removed the relevent tests from exclusion lists.

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[gemini-code-assist]

Code Review

This pull request enables previously excluded tests for the OpenVINO backend and updates the pad operation in keras/src/backend/openvino/numpy.py to support float constant values. Feedback was provided to further expand the type validation for constant_values to include NumPy scalar types, ensuring compatibility with common Keras data types and preventing unnecessary errors.

[codecov-commenter]

Codecov Report

❌ Patch coverage is 0% with 1 line in your changes missing coverage. Please review.
✅ Project coverage is 82.95%. Comparing base (d51c980) to head (7e926ae).
⚠️ Report is 4 commits behind head on master.

Files with missing lines	Patch %	Lines
keras/src/backend/openvino/numpy.py	0.00%	0 Missing and 1 partial ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #22691      +/-   ##
==========================================
+ Coverage   82.94%   82.95%   +0.01%     
==========================================
  Files         596      596              
  Lines       69200    69252      +52     
  Branches    10806    10814       +8     
==========================================
+ Hits        57399    57451      +52     
  Misses       8973     8973              
  Partials     2828     2828              

Flag	Coverage Δ
keras	82.77% <0.00%> (+0.01%)	⬆️
keras-jax	58.72% <0.00%> (-0.04%)	⬇️
keras-numpy	54.56% <0.00%> (-0.04%)	⬇️
keras-openvino	59.43% <0.00%> (+0.04%)	⬆️
keras-tensorflow	60.28% <0.00%> (-0.04%)	⬇️
keras-torch	59.05% <0.00%> (-0.05%)	⬇️

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[hertschuh]

Thanks for the fix!