Separate kwargs of tokenizer and feature_extractor in `ClapProcessor`
Author: anmolojha
Pull request: yes

# What does this PR do?
Currently, `ClapProcessor` shares kwargs between the tokenizer and the feature extractor. This PR introduces separate kwargs for both of them.

This was discussed in [comments](https://github.com/huggingface/transformers/issues/23648#issuecomment-1557532041) of #23648. 
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Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @sgugger

Integrations:

- deepspeed: HF Trainer/Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam

Documentation: @sgugger, @stevhliu and @MKhalusova

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: @sgugger
- TensorFlow: @Rocketknight1

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@sanchit-gandhi 

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_24503). All of your documentation changes will be reflected on that endpoint.

@sanchit-gandhi can we fix both the points discussed in the issue (#23648) (shared kwargs and unexpected padding behaviour) in the same PR or should we have separate PRs?

Separate PR would be preferable since you can work on each bit in isolation (making it easier for yourself and the reviewer) and merge this one as soon as you have it ready :)

Think it's going to be quite fast to finish this PR - WDYT @anmolojha?

Hey @sanchit-gandhi, thanks for following up 🙏
This got delayed because of a bunch of reasons, I will close this this weekend.

Awesome! Looking forward to it @anmolojha!

Would like the tokenizer expert's review cc @ArthurZucker 

Gently pinging @ArthurZucker for a final review here

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.

Do you want to have a go at explicitly writing out the required args for the feature extractor / tokenizer @anmolojha? It should make the signature for the `__call__` method more precise as @ArthurZucker astutely mentioned.