Fix torch only support for fast Processors

[Blaizzy]

What does this PR do?

Adds MLX tensor support to BatchFeature and removes the PyTorch-only restriction in fast image processing utilities.

Changes:

• Added is_mlx_array export to transformers/utils/__init__.py
• Implemented MLX tensor conversion logic in BatchFeature.convert_to_tensors() (feature_extraction_utils.py)
• Removed the hardcoded validation that restricted fast image processors to PyTorch tensors only (image_processing_utils_fast.py)

This enables using return_tensors="mlx" with vision models and fast image processors on Apple Silicon, which previously raised:

ValueError: Only returning PyTorch tensors is currently supported. 

Before submitting

• This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
• Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
  Pull Request section?
• Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
  to it if that's the case.
• Did you make sure to update the documentation with your changes? Here are the
  [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
  [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
• Did you write any new necessary tests?

Who can review?

• @yonigozlan @molbap (vision models / image processing)
• @ArthurZucker (library / model loading)

[Rocketknight1]

cc @yonigozlan @molbap but not sure who to tag for MLX!

[Blaizzy]

@ArthurZucker has some context as well

[github-actions]

[For maintainers] Suggested jobs to run (before merge)

run-slow: pop2piano

[github-actions]

View the CircleCI Test Summary for this PR:

https://huggingface.co/spaces/transformers-community/circle-ci-viz?pr=42824&sha=ed0abd