Add matrix power operation to linalg API and backend implementations

[buildwithsuhana]

Description

This PR introduces the matrix_power operation to the keras.ops.linalg module, providing a unified API to raise square matrices to an integer power n across all supported backends.

matrix_power is a fundamental operation in linear algebra with several critical applications in machine learning, physics, and computer science.

The keras.ops.linalg.matrix_power(x, n) operation raises a square matrix (or a batch of square matrices) to the integer power n.

• If $n > 0$: The matrix is multiplied by itself $n$ times (calculated efficiently via binary exponentiation).
• If $n = 0$: Returns the identity matrix of the same shape as x.
• If $n < 0$: Computes the matrix inverse $x^{-1}$ and then raises it to the power $|n|$.

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[gemini-code-assist]

Code Review

This pull request introduces the matrix_power operation to Keras linear algebra operations (keras.ops.linalg), implementing it across all supported backends (JAX, NumPy, OpenVINO, TensorFlow, and PyTorch) along with corresponding unit tests. The review feedback highlights two important issues: first, the OpenVINO backend implementation passes raw Python integers to opset functions instead of Node or Output objects, which can cause compilation or runtime failures; second, the non-symbolic execution path in _matrix_power lacks validation to ensure n is an integer, which could lead to infinite loops or incorrect behavior in backends like TensorFlow and OpenVINO if a float is provided.

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[codecov-commenter]

Codecov Report

❌ Patch coverage is 58.62069% with 36 lines in your changes missing coverage. Please review.
✅ Project coverage is 84.01%. Comparing base (2aeecf0) to head (cce3ec7).
⚠️ Report is 1 commits behind head on master.

Files with missing lines	Patch %	Lines
keras/src/backend/openvino/linalg.py	17.07%	31 Missing and 3 partials ⚠️
keras/src/ops/linalg.py	91.66%	1 Missing and 1 partial ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #23227      +/-   ##
==========================================
- Coverage   84.80%   84.01%   -0.80%     
==========================================
  Files         465      465              
  Lines       69201    69288      +87     
  Branches    11379    11398      +19     
==========================================
- Hits        58687    58212     -475     
- Misses       7577     8147     +570     
+ Partials     2937     2929       -8     

Flag	Coverage Δ
keras	83.83% <58.62%> (-0.78%)	⬇️
keras-cpu	83.83% <58.62%> (-0.04%)	⬇️
keras-gpu	?
keras-jax	57.88% <31.03%> (-0.38%)	⬇️
keras-numpy	53.67% <31.03%> (-0.03%)	⬇️
keras-openvino	59.51% <36.78%> (-0.03%)	⬇️
keras-tensorflow	59.49% <47.12%> (-0.31%)	⬇️
keras-torch	58.62% <31.03%> (-0.44%)	⬇️
keras-tpu	?

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