feat: add pipeline registry abstraction
# What does this PR do?

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- added `PipelineRegistry` abstraction for better supports for custom pipeline. 
- updates `add_new_pipeline.mdx` (english docs) to reflect the api addition
- migrate `check_task` and `get_supported_tasks` from
  `transformers/pipelines/__init__.py` to
 ` transformers/pipelines/base.py#PipelineRegistry.{check_task,get_supported_tasks}`

Address #17762


## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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      to it if that's the case.
- [x] Did you make sure to update the documentation with your changes? Here are the
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      [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?

@LysandreJik and @sgugger, would be great if you guys can provide feedback.

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Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->

_The documentation is not available anymore as the PR was closed or merged._<|||||>> Note that this is only to customize preprocessing and/or postprocessing as this still relies on existing auto-model classes.

Should I include inside the docs to use an `AutoModel` class for better readability?<|||||>@Narsil CI failed due to the recent `black` versioning locked?<|||||>Super nice PR thanks for this addition !

Left a few NITs about the structure. Feel free to ignore if you don't agree with them<|||||>> @Narsil CI failed due to the recent `black` versioning locked?

Seems like `black` released a new version and the CI is not locking it, right @sgugger  ?
https://pypi.org/project/black/<|||||>Yes, you'll need to rebase on main to fix the tests. Failures are due to new releases of black and PyTorch.<|||||>> Yes, you'll need to rebase on main to fix the tests. Failures are due to new releases of black and PyTorch.

understood. Address accordingly.

cc @LysandreJik @sgugger @Narsil when you guys have time.<|||||>That's very nice, love this approach! Should make it much much simpler to add custom pipelines.

I only have one request: please add tests :smile: <|||||>cc @LysandreJik for tests. I'm thinking to add a test for log capture output, but I'm not too familiar with transformers logging structure.<|||||>If you want to test outputs, we have a util for this called `CaptureStd`. You can see an example of use in [this test](https://github.com/huggingface/transformers/blob/9fe2403bc52e342022ed132561655f84a6b6b7f3/tests/utils/test_cli.py#L30).<|||||>> If you want to test outputs, we have a util for this called `CaptureStd`. You can see an example of use in [this test](https://github.com/huggingface/transformers/blob/9fe2403bc52e342022ed132561655f84a6b6b7f3/tests/utils/test_cli.py#L30).

Thanks. Will update accordingly.<|||||>tests are finished. lmk if any additional testing is required. cc @LysandreJik <|||||>Failure is flaky, so merging. Thanks again for your contribution!