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If `torch.hub` is never used, the cache directory "~/.cach/torch/hub/checkpoints/" does not exist,
and the attempt to download DeepPhonemizer checkpoint there would fail.

This commit fixes it by calling `os.makedirs(directory, exit_ok=True)`.

1. Override the return type so that Sphinx shows the exported symbols.
   (output model types and input torch.nn.Module)
2. Tweak docs for Tacotron2TTSBundle interfaces
3. Fix for HUBERT_ASR_XLARGE

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

To handle batched input properly.

Move the computation of `#classes -> #bits` to the constructor of WaveRNN and attach it to the instance, so that it can be reused elsewhere.

This commit merges wav2vec2/hubert factory functions for pre-training and fine-tuning. In #1829, we added parameters to customize the models that are not part of architecture, and `aux_num_out` falls into this category, so it is no longer necessary to have separate functions. This concludes the wav2vec2/HuBERT API update in release 0.10.

The summary of BC-breaking changes on wav2vec2 APIs between 0.9 and 0.10 (when this commit is incorporated)
1. `Wav2Vec2Model.extract_features`
In 0.9, it was returning the output from `FeatureExtractor` module. In 0.10, it returns the list of outputs from the intermediate layers of `TransformerEncoder` block.
2. `wav2vec2_base(num_out: int)` -> `wav2vec2_base(<dropout_params:float>, aux_num_out: Optional[int]=None)`
    - `num_out` was renamed to `aux_num_out` and optional. If it is omitted, the resulting model does not have the linear layer for fine-tuning.
    - Added dropout parameters.