Fix FP16 inference in TextGenerationPipeline
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Hi @Narsil,

I tried to fix https://github.com/huggingface/transformers/issues/20912 here by settiing `torch_dtype` as a regular attribute to help with the `preprocess` function in `AutomaticSpeechRecognitionPipeline`. This way we keep it out of `kwargs`, so don't need to modify the `_sanitize_parameters` function in other pipelines. Looking forward to hearing your opinion :)


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Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts and @NielsRogge
- speech models: @sanchit-gandhi

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @sgugger

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

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: @sgugger
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_The documentation is not available anymore as the PR was closed or merged._<|||||>In general its better for parameters to be  in `_sanitize_parameters` but this doesn't apply here, since the models already uses `torch_dtype` and so using `pipe(..., torch_dtype=torch.float16)` cannot work anyway.

 I think the proposed fix is elegant.

Do you mind adding a test for `text-generation` and `float16` too ? 

For the quality you should be able to do

```
pip install -e .[dev] # To get dependencies
make fixup
```<|||||>Thanks for the review @Narsil !

Do you think it should be better to change the name `torch_dtype` to `dtype`, since `Pipeline` can also be used for Tensorflow? I don't really use Tensorflow so I'm not sure about it.

Just add a test and fix the quality. Thanks for the tips!
<|||||>> Do you think it should be better to change the name torch_dtype to dtype, since Pipeline can also be used for Tensorflow? I don't really use Tensorflow so I'm not sure about it.

Later if we do it. Better stick to the named used elsewhere in the lib which is indeed `torch_dtype`. I'm also unfamiliar with fp16 computation in Tensorflow, but I'm guessing it could work differently.

The good thing is that we could always alias later if needed.