Return effective attention mask in Wav2Vec2BaseModelOutput
Author: gau-nernst
Pull request: yes

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Fixes #25307 

- Add field `attention_mask` to Wav2Vec2BaseModelOutput
- Return updated attention mask for Wav2VecModel, Data2VecAudioModel, HubertModel, SEWModel, SEWDModel, WavLMModel, Wav2Vec2ConformerModel, UniSpeechModel, UniSpeechSatModel
- Change model output from BaseModelOutput to Wav2Vec2BaseModelOutput for HubertModel, SEWModel, SEWDModel
- Fix tensor comparison functions to accept bool

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Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_25471). All of your documentation changes will be reflected on that endpoint.

@sanchit-gandhi How should I add a test checking for returned downsampled attention mask? Should it be under `Wav2Vec2ModelTest`? I'm not familiar with HF tests, and it looks kinda overwhelming.

Hey @gau-nernst - indeed it's quite an intimidating file! It's got quite a lot of tests given Wav2Vec2 is a core model in the library and we want to ensure that any new changes don't break backwards compatibility. But once you know how it works it's quite straightforward!

The model tester class defines all the functions we want to test (`check_xxx`). The model test class then executes them (`test_xxx`).

What I would suggest doing here is defining a function in the model tester, e.g. https://github.com/huggingface/transformers/blob/450a181d8b963b4e896be4aac701815aa554a6bb/tests/models/wav2vec2/test_modeling_wav2vec2.py#L462

And then running the test in the model test, e.g. https://github.com/huggingface/transformers/blob/450a181d8b963b4e896be4aac701815aa554a6bb/tests/models/wav2vec2/test_modeling_wav2vec2.py#L546

=> this way you just have to focus on writing one new function in the model tester, and then execute it in the model test

In this test, I think we can check that:
1. We return an attention mask from the model output
2. This attention mask has the correct downsampled length (which we can get from the private method `_get_feat_extract_output_lengths` if required)

It's looking very close to completion @gau-nernst! Just the `return_dict` situation that needs addressing, otherwise in good shape 🤗

Let me know when you'd like a re-review here @gau-nernst! It's looking quite nice already!

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.

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