Add FastImageProcessor for EfficientNet

[chewyuenrachael]

Add FastImageProcessor for EfficientNet

What does this PR do?

This PR implements a FastImageProcessor for the EfficientNet model using BaseImageProcessorFast.

• Added EfficientNetImageProcessorFast to support fast GPU-based preprocessing using PyTorch/Torchvision ops
• Verified default values (e.g., size, crop_size, normalization) match the existing slow processor
• Cleaned out unused attributes (default_to_square, do_convert_rgb) after comparing both implementations
• Updated the test file test_image_processing_efficientnet.py to support both fast and slow processors using image_processor_list pattern
• Verified that all relevant tests pass with RUN_SLOW=1

This PR contributes to [#36978](#36978)

Before submitting

• I have read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request)
• This PR was initiated via a GitHub issue: [Contributions Welcome] Add Fast Image Processors #36978
• I have matched default attributes between the slow and fast image processors
• I have updated test coverage to loop over both slow and fast processors
• I have verified all tests pass with RUN_SLOW=1
• I ran black and make fixup to format the code
• Documentation did not need updating (no new public methods introduced)
• All new methods follow the docstring conventions

Who can review?

This contribution affects vision models.
Tagging: @qubvel @amyeroberts for review.

Thanks in advance! 🤗

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