Add support for Magcache

[AlanPonnachan]

What does this PR do?

This PR adds support for MagCache , a training-free inference acceleration method for diffusion models, specifically targeting Transformer-based architectures like Flux.

This implementation follows the ModelHook pattern (similar to FirstBlockCache) to integrate seamlessly into Diffusers.

Key features:

• MagCacheConfig: Configuration class to control threshold, retention ratio, and skipping limits.
• apply_mag_cache: Helper function to attach the hooks to a model.
• Default Ratios: Includes pre-computed magnitude decay ratios for Flux models (Dev/Schnell) as per the official implementation.
• Mechanism: The hook calculates the accumulated error of the residual magnitude at each step. If the error is below the defined threshold, it skips the computation of the transformer blocks and approximates the output using the residual from the previous step.

Fixes #12697

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?
• Did you read our philosophy doc (important for complex PRs)?
• Was this discussed/approved via a GitHub issue or the forum? Please add a link to it if that's the case. (Magcache Support. #12697)
• Did you make sure to update the documentation with your changes? Here are the
  documentation guidelines, and
  here are tips on formatting docstrings.
• Did you write any new necessary tests?

Who can review?

@sayakpaul

[sayakpaul]

@leffff could you review as well if possible?