GitLab

Summary:
Applies new import merging and sorting from µsort v1.0.

When merging imports, µsort will make a best-effort to move associated
comments to match merged elements, but there are known limitations due to
the diynamic nature of Python and developer tooling. These changes should
not produce any dangerous runtime changes, but may require touch-ups to
satisfy linters and other tooling.

Note that µsort uses case-insensitive, lexicographical sorting, which
results in a different ordering compared to isort. This provides a more
consistent sorting order, matching the case-insensitive order used when
sorting import statements by module name, and ensures that "frog", "FROG",
and "Frog" always sort next to each other.

For details on µsort's sorting and merging semantics, see the user guide:
https://usort.readthedocs.io/en/stable/guide.html#sorting

Reviewed By: lisroach

Differential Revision: D36402214

fbshipit-source-id: b641bfa9d46242188524d4ae2c44998922a62b4c

Summary:
Applies the black-fbsource codemod with the new build of pyfmt.

paintitblack

Reviewed By: lisroach

Differential Revision: D36324783

fbshipit-source-id: 280c09e88257e5e569ab729691165d8dedd767bc

Summary:
PyTorch Lite, which is becoming a standard for mobile PyTorch usage, does not support containers containing custom classes. Consequently, because TorchAudio's RNN-T decoder currently returns and accepts lists of `Hypothesis` namedtuples, it is not compatible with PyTorch Lite. This PR resolves said incompatibility by changing the underlying implementation of `Hypothesis` to tuple.

Pull Request resolved: https://github.com/pytorch/audio/pull/2339

Reviewed By: nateanl

Differential Revision: D35806529

Pulled By: hwangjeff

fbshipit-source-id: 9cbae5504722390511d35e7f9966af2519ccede5

Summary:
- Refactor the current `LibriSpeechRNNTModule`'s unit test.
- Add unit tests for `TEDLIUM3RNNTModule` and `MuSTCRNNTModule`
- Replace the lambda with partial in `TEDLIUM3RNNTModule` to pass the lightning unit test.

Pull Request resolved: https://github.com/pytorch/audio/pull/2240

Reviewed By: mthrok

Differential Revision: D34285195

Pulled By: nateanl

fbshipit-source-id: 4f20749c85ddd25cbb0eafc1733c64212542338f

Summary:
This PR adds ``EMFORMER_RNNT_BASE_MUSTC`` support in `pipeline_demo.py`. The bundle is trained on MuST-C release 2.0 dataset. The model  preserves the casing and punctuations in the transcript.

Here is a screen recording of how it works in streaming and non-streaming modes:

https://user-images.githubusercontent.com/8653221/154356521-fe84bdc1-fb0c-41bd-8729-9edbb3224a07.mov

Pull Request resolved: https://github.com/pytorch/audio/pull/2248

Reviewed By: hwangjeff

Differential Revision: D34282598

Pulled By: nateanl

fbshipit-source-id: 42ed7e2623031dfebd176ef0c6bfd70da3c897d4

Summary:
- Use dictionary to select the `RNNTBundle` and the corresponding dataset.
- Use the dictionary's keys as choices in ArgumentParser

Pull Request resolved: https://github.com/pytorch/audio/pull/2239

Reviewed By: mthrok

Differential Revision: D34267070

Pulled By: nateanl

fbshipit-source-id: 99c7942d5c7c1518694e1ae02a55a7decd87c220

Summary:
- Add docstring to `eval.py` and `pipeline_demo.py` under `emformer_rnnt` directory.
- Refactor logger and ArgumentParser

Pull Request resolved: https://github.com/pytorch/audio/pull/2238

Reviewed By: mthrok

Differential Revision: D34267059

Pulled By: nateanl

fbshipit-source-id: 4b8d3d183ee7bc0ad71ce305cab87bfa90208b2e

Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2237

Reviewed By: mthrok

Differential Revision: D34267000

Pulled By: nateanl

fbshipit-source-id: 4c264aea6cf3fba5d8728d5fe60f9f471815852d

Summary:
Replace underscore with dash in ArgumentParser's arguments.

Pull Request resolved: https://github.com/pytorch/audio/pull/2236

Reviewed By: mthrok

Differential Revision: D34266977

Pulled By: nateanl

fbshipit-source-id: ceacac12c04016a8dbf2a1a7d6bbcf65d4d53d21

Summary:
- Add a MUSTC dataset under examples
- Add a lightning module for MuST-C dataset
- Refactor `train.py`, `eval.py`, and `global_stats.py` scripts

Pull Request resolved: https://github.com/pytorch/audio/pull/2219

Reviewed By: hwangjeff

Differential Revision: D34180466

Pulled By: nateanl

fbshipit-source-id: 9fc74ce7527da1a81dd0738e124428f9d516d164

Summary:
Adds SentencePiece model training script for LibriSpeech Emformer RNN-T example recipe; updates readme with references.

Pull Request resolved: https://github.com/pytorch/audio/pull/2218

Reviewed By: nateanl

Differential Revision: D34177295

Pulled By: hwangjeff

fbshipit-source-id: 9f32805af792fb8c6f834f2812e20104177a6c43

Summary:
We refactored the demo script that can apply RNNT decoding using both `torchaudio.pipelines.EMFORMER_RNNT_BASE_LIBRISPEECH` and `torchaudio.prototype.pipelines.EMFORMER_RNNT_BASE_TEDLIUM3` in both streaming and non-streaming mode. (The first hypothesis prediction is streaming and the second one is non-streaming).

We convert each token id sequence to word pieces and then manually join the word pieces. This allows us to preserve leading whitespaces on output strings and therefore account for word breaks and continuations across token processor invocations, which is particularly useful when performing streaming ASR.

https://user-images.githubusercontent.com/8653221/153627956-f0806f18-3c1c-44df-ac07-ec2def58a0cf.mov

Pull Request resolved: https://github.com/pytorch/audio/pull/2203

Reviewed By: carolineechen

Differential Revision: D34006388

Pulled By: nateanl

fbshipit-source-id: 3d31173ee10cdab8a2f5802570e22b50fcce5632

Summary:
Adds unit tests for Emformer RNN-T LibriSpeech recipe. Also makes changes to recipe to resolve errors with pickling lambda functions in Windows.

Pull Request resolved: https://github.com/pytorch/audio/pull/2216

Reviewed By: nateanl

Differential Revision: D34171480

Pulled By: hwangjeff

fbshipit-source-id: 5fcebb457051f3041766324863728411180f5e1e

Summary:
- Removes 100-batch truncation in TEDLIUM3 recipe.
- Reinstates `train_spm.py` for TEDLIUM3.

Pull Request resolved: https://github.com/pytorch/audio/pull/2217

Reviewed By: nateanl

Differential Revision: D34171525

Pulled By: hwangjeff

fbshipit-source-id: 54698e5e1b094c26c28eec9b8b1722223077876c

Summary:
Consolidates LibriSpeech and TED-LIUM Release 3 Emformer RNN-T training recipes in a single directory.

Pull Request resolved: https://github.com/pytorch/audio/pull/2212

Reviewed By: mthrok

Differential Revision: D34120104

Pulled By: hwangjeff

fbshipit-source-id: 29c6e27195d5998f76d67c35b718110e73529456