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Summary:
In recent updates, torchaudio added features that download assets/models from
download.pytorch.org/torchaudio.

To reduce the code duplication, the implementations uses utilities from
``torch.hub``, but still, there are patterns repeated in implementing
the fetch mechanism, notably cache and local file path handling.

This commit introduces the utility function that handles
download/cache/local path management that can be used for
fetching pre-trained model data.

Pull Request resolved: https://github.com/pytorch/audio/pull/2283

Reviewed By: carolineechen

Differential Revision: D35050469

Pulled By: mthrok

fbshipit-source-id: 219dd806f9a96c54d2d31e981c1bbe282772702b

Summary:
Moves ASR features out of `torchaudio.prototype`. Specifically, merges contents of `torchaudio.prototype.models` into `torchaudio.models` and contents of `torchaudio.prototype.pipelines` into `torchaudio.pipelines` and updates refs, tests, and docs accordingly.

Pull Request resolved: https://github.com/pytorch/audio/pull/2187

Reviewed By: nateanl, mthrok

Differential Revision: D33918092

Pulled By: hwangjeff

fbshipit-source-id: f003f289a7e5d7d43f85b7c270b58bdf2ed6344c

Summary:
Adds integration test for pretrained ASR pipeline `EMFORMER_RNNT_BASE_LIBRISPEECH`.

Pull Request resolved: https://github.com/pytorch/audio/pull/2172

Reviewed By: carolineechen, nateanl

Differential Revision: D33793324

Pulled By: hwangjeff

fbshipit-source-id: d0613e2ab98fe5afa7b16ca39b67f0a0304d13fc

Summary:
cc mthrok

Pull Request resolved: https://github.com/pytorch/audio/pull/2116

Reviewed By: mthrok

Differential Revision: D33368453

Pulled By: jdsgomes

fbshipit-source-id: 09cf3fe5ed6f771c2f16505633c0e59b0c27453c

Summary:
Pull Request resolved: https://github.com/pytorch/audio/pull/2096

run: `arc lint --apply-patches --paths-cmd 'hg files -I "./**/*.py"'`

Reviewed By: mthrok

Differential Revision: D33297351

fbshipit-source-id: 7bf5956edf0717c5ca90219f72414ff4eeaf5aa8

This commit changes all the `torch.hub` network utility functions to
be imported from `torchaudio._internal`, so that later we can replace
the function within fbcode.

* Add wav2vec2 ASR German pretrained model from voxpopuli

- Make the test support other languages
- Fetch tetst asset on-the-fly

* [BC-breaking] Remove unused dimension from pretrained Wav2Vec2 ASR

The Wav2Vec2 ASR pretrained weights originated from fairseq have
extra dimension that have nothing to do with the ASR task.

https://github.com/pytorch/fairseq/blob/c5ff181125c7e6126b49a85e5ebdd5f5b6a07914/fairseq/data/dictionary.py#L18-L37

which is masked during the loss computation as

https://github.com/pytorch/fairseq/blob/c5ff181125c7e6126b49a85e5ebdd5f5b6a07914/fairseq/criterions/ctc.py#L126-L128

This change removes it.

* Use '-' for blank token representation.

Future work items:
- length computation of GriffinLim
- better way to make InverseMelScale work in inference_mode

- Move wav2vec2 pretrained weights to `torchaudio.pipelines` namespace to align with #1872.
- Split `Wav2Vec2PretrainedModelBundle` into `Wav2Vec2Bundle` (for pre-training model) and  `Wav2Vec2ASRBundle` (for models fine-tuned for ASR).
- Update base URL

Add pretrained weights from https://github.com/pytorch/fairseq/tree/main/examples/wav2vec#pre-trained-models
- Wav2Vec 2.0 Base / Large / Large (LV-60)
- XLSR-53

This commit adds
- HUBERT_LARGE
- HUBERT_XLARGE
- HUBERT_ASR_XLARGE