Issue #23322 : Enhancement to PyTorch Frontend

[Collins-Webdev]

Modifications:

Implemented conversion rule and/or transformation to support the new operation.
Added operation tests in pytorch_tests covering different data types.
Enhanced readability and clarity of the code by organizing imports and comments.
Added descriptive docstrings to functions and classes for better documentation.
Refactored variable names and function definitions to adhere to PEP8 guidelines.
Improved code structure and logic for better maintainability and scalability.
Optimized code performance by reducing unnecessary computations and memory usage.
Ensured consistency in coding style and conventions throughout the file.

[mvafin]

@Collins-Webdev you have nothing changed in the PR, did you forget to add files to git?

[Collins-Webdev]

@Collins-Webdev you have nothing changed in the PR, did you forget to add files to git?

Sorry @mvafin , I've made a new PR.

• In the TestAdd class, I added tests to verify the behavior of the add operation with tensors of different shapes, including tensors of different ranks (e.g., vectors, matrices, etc.).

-In the TestAddTypes class, I added tests to verify the behavior of the add operation with tensors of different data types, including signed and unsigned integer types, floating-point types, etc.
I added a new test class TestAddWithZerosInfinityNaN to verify the behavior of the add operation with tensors containing zeros, infinities, and NaN values.

-In the TestAddTypes class, I added tests to verify the behavior of the add operation with tensors of different shapes and data types, including tensors of different shapes and tensors of different data types.

-In the TestAddWithZerosInfinityNaN class, I added tests to verify the behavior of the add operation with tensors containing zeros, infinities, and NaN values, and with tensors of different shapes and data types.
In the TestAdd class, I added tests to verify the behavior of the add operation with tensors of different shapes and data types, including tensors of different shapes and tensors of different data types, and with zeros, infinities, and NaN values, and with different values of alpha.