Update kwargs validation for `preprocess` with decorator
Author: qubvel
Pull request: yes

# What does this PR do?

Update most of the image processors with `filter_out_non_signature_kwargs` decorator for kwargs validation instead of `_valid_processor_keys` (continue of work started in https://github.com/huggingface/transformers/pull/30799)

## Before submitting
- [x] 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).
- [x] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- text models: @ArthurZucker
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

 -->


Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32024). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

CLIP/Git image processors require updating their processors first, DETR* image processors require adding deprecation. In this PR **only** simple cases are handled, where we need to replace `_valid_processor_keys` with a decorator, other cases will be done in follow-up PRs for review simplicity.

@molbap whenever you have time, please have a look

@molbap `inspect.signature` is used only once the class method when the class is defined (on class import), so I would not expect any slowdown. Even if we have 1k imports of objects overall it should not take longer than a fraction of a second. Am I missing something here? Afair, you choose to use `_valid_processor_kwargs` instead `inspect.signature`, was there any specific reason?

Yes you're right, it's only at import time. I was just curious since inspect-related calls have ended up costing me some precious ms before, so I steer away from it

@amyeroberts please review whenever you have time