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  1. 25 Jul, 2023 1 commit
  3. 18 Jul, 2023 1 commit
  5. 28 Jun, 2023 1 commit
  7. 21 Jun, 2023 1 commit
  9. 24 May, 2023 1 commit
  11. 23 May, 2023 1 commit
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  17. 29 Apr, 2023 1 commit
  19. 28 Apr, 2023 1 commit
    • Yuekai Zhang's avatar
      Add cuctc decoder (#3096) · 0a1801ed
      Yuekai Zhang authored 
      Summary:
This PR implements a CUDA based ctc prefix beam search decoder.

Attach serveral benchmark results using V100 below:
|decoder type| model |datasets       | decoding time (secs)| beam size | batch size | model unit | subsampling times | vocab size |
|--------------|---------|------|-----------------|------------|-------------|------------|-----------------------|------------|
| cuctc |  conformer nemo    |dev clean        |7.68s | 8           |  32       | bpe         |    4  | 1000|
| cuctc |  conformer nemo   |dev clean  (sort by length)      |1.6s | 8           |  32       | bpe         |    4  | 1000|
| cuctc |  wav2vec2.0 torchaudio |dev clean                                |22s | 10           |  1       | char         |    2  | 29|
| cuctc |   conformer espnet   |aishell1 test                             | 5s | 10           |  24       | char         |    4  | 4233|

Note:
1.  The design is to parallel computation through batch and vocab axis, for loop the frames axis. So it's more friendly with smaller sequence lengths, larger vocab size comparing with CPU implementations.
2. WER is the same as CPU implementations. However, it can't decode with LM now.

Resolves: https://github.com/pytorch/audio/issues/2957.

Pull Request resolved: https://github.com/pytorch/audio/pull/3096

Reviewed By: nateanl

Differential Revision: D44709397

Pulled By: mthrok

fbshipit-source-id: 3078c54a2b44dc00eb4a81b4c657487eeff8c155
      0a1801ed
  21. 11 Feb, 2023 1 commit
  23. 07 Feb, 2023 1 commit
  25. 01 Feb, 2023 1 commit
  27. 30 Dec, 2022 1 commit
  29. 17 Dec, 2022 1 commit
  31. 07 Dec, 2022 1 commit
  33. 29 Nov, 2022 1 commit
  35. 28 Nov, 2022 1 commit
  37. 15 Nov, 2022 1 commit
  39. 08 Nov, 2022 1 commit
  41. 02 Nov, 2022 1 commit
  43. 28 Oct, 2022 1 commit
  45. 23 Sep, 2022 1 commit
  47. 15 Sep, 2022 1 commit
  49. 15 Aug, 2022 1 commit
  51. 05 Aug, 2022 1 commit
    • hwangjeff's avatar
      Add convolution operator (#2602) · b396157d
      hwangjeff authored 
      Summary:
Adds functions `convolve` and `fftconvolve`, which compute the convolution of two tensors along their trailing dimension. The former performs the convolution directly, whereas the latter performs it using FFT.

Pull Request resolved: https://github.com/pytorch/audio/pull/2602

Reviewed By: nateanl, mthrok

Differential Revision: D38450771

Pulled By: hwangjeff

fbshipit-source-id: b2d1e063ba21eafeddf317d60749e7120b14292b
      b396157d
  53. 28 Jul, 2022 1 commit
    • Sean Kim's avatar
      Create tutorial for HDemucs (#2572) · 919fd0c4
      Sean Kim authored 
      Summary:
Add tutorial python file, draft PR, will continue to modify accordingly to feedback.

Future plan: modify spectrogram and bottom audio design and work on finding best audio track and segments

Pull Request resolved: https://github.com/pytorch/audio/pull/2572

Reviewed By: carolineechen, nateanl, mthrok

Differential Revision: D38234001

Pulled By: skim0514

fbshipit-source-id: fe9207864f354dec5cf5ff52bf7d9ddcf4a001d5
      919fd0c4
  55. 08 Jun, 2022 1 commit
  57. 01 Jun, 2022 1 commit
    • Caroline Chen's avatar
      Move CTC beam search decoder to beta (#2410) · 93024ace
      Caroline Chen authored 
      Summary:
Move CTC beam search decoder out of prototype to new `torchaudio.models.decoder` module.

hwangjeff mthrok any thoughts on the new module + naming, and if we should move rnnt beam search here as well??

Pull Request resolved: https://github.com/pytorch/audio/pull/2410

Reviewed By: mthrok

Differential Revision: D36784521

Pulled By: carolineechen

fbshipit-source-id: a2ec52f86bba66e03327a9af0c5df8bbefcd67ed
      93024ace
  59. 20 May, 2022 1 commit
  61. 13 May, 2022 1 commit
    • moto's avatar
      Move Streamer API out of prototype (#2378) · 72b712a1
      moto authored 
      Summary:
This commit moves the Streaming API out of prototype module.

* The related classes are renamed as following

  - `Streamer` -> `StreamReader`.
  - `SourceStream` -> `StreamReaderSourceStream`
  - `SourceAudioStream` -> `StreamReaderSourceAudioStream`
  - `SourceVideoStream` -> `StreamReaderSourceVideoStream`
  - `OutputStream` -> `StreamReaderOutputStream`

This change is preemptive measurement for the possibility to add
`StreamWriter` API.

* Replace BUILD_FFMPEG build arg with USE_FFMPEG

We are not building FFmpeg, so USE_FFMPEG is more appropriate

 ---

After https://github.com/pytorch/audio/issues/2377

Remaining TODOs: (different PRs)
- [ ] Introduce `is_ffmpeg_binding_available` function.
- [ ] Refactor C++ code:
   - Rename `Streamer` to `StreamReader`.
   - Rename `streamer.[h|cpp]` to `stream_reader.[h|cpp]`.
   - Rename `prototype.cpp` to `stream_reader_binding.cpp`.
   - Introduce `stream_reader` directory.
- [x] Enable FFmpeg in smoke test (https://github.com/pytorch/audio/issues/2381)

Pull Request resolved: https://github.com/pytorch/audio/pull/2378

Reviewed By: carolineechen

Differential Revision: D36359299

Pulled By: mthrok

fbshipit-source-id: 6a57b702996af871e577fb7addbf3522081c1328
      72b712a1
  63. 12 Apr, 2022 1 commit
    • hwangjeff's avatar
      Add Conformer RNN-T model prototype (#2322) · b0c8e239
      hwangjeff authored 
      Summary:
Adds Conformer RNN-T model as prototype feature, by way of factory functions `conformer_rnnt_model` and `conformer_rnnt_base`, which instantiates a baseline version of the model. Also includes the following:
- Modifies `Conformer` to accept arguments `use_group_norm` and `convolution_first` to pass to each of its `ConformerLayer` instances.
- Makes `_Predictor` an abstract class and introduces `_EmformerEncoder` and `_ConformerEncoder`.
- Introduces tests for `conformer_rnnt_model`.
- Adds docs.

Pull Request resolved: https://github.com/pytorch/audio/pull/2322

Reviewed By: xiaohui-zhang

Differential Revision: D35565987

Pulled By: hwangjeff

fbshipit-source-id: cb37bb0477ae3d5fcf0b7124f334f4cbb89b5789
      b0c8e239
  65. 08 Apr, 2022 1 commit
    • moto's avatar
      Add devices/properties badges (#2321) · 72ae755a
      moto authored 
      Summary:
Add badges of supported properties and devices to functionals and transforms.

This commit adds `.. devices::` and `.. properties::` directives to sphinx.

APIs with these directives will have badges (based off of shields.io) which link to the
page with description of these features.

Continuation of https://github.com/pytorch/audio/issues/2316
Excluded dtypes for further improvement, and actually added badges to most of functional/transforms.

Pull Request resolved: https://github.com/pytorch/audio/pull/2321

Reviewed By: hwangjeff

Differential Revision: D35489063

Pulled By: mthrok

fbshipit-source-id: f68a70ebb22df29d5e9bd171273bd19007a81762
      72ae755a
  67. 26 Feb, 2022 1 commit
    • moto's avatar
      Improve device streaming (#2202) · 365313ed
      moto authored 
      Summary:
This commit adds tutorial for device ASR, and update API for device streaming.

The changes for the interface are
1. Add `timeout` and `backoff` parameters to `process_packet` and `stream` methods.
2. Move `fill_buffer` method to private.

When dealing with device stream, there are situations where the device buffer is not
ready and the system returns `EAGAIN`. In such case, the previous implementation of
`process_packet` method raised an exception in Python layer , but for device ASR,
this is inefficient. A better approach is to retry within C++ layer in blocking manner.
The new `timeout` parameter serves this purpose.

Pull Request resolved: https://github.com/pytorch/audio/pull/2202

Reviewed By: nateanl

Differential Revision: D34475829

Pulled By: mthrok

fbshipit-source-id: bb6d0b125d800f87d189db40815af06fbd4cab59
      365313ed
  69. 04 Feb, 2022 1 commit
  71. 03 Feb, 2022 1 commit
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  75. 01 Feb, 2022 1 commit
  77. 29 Dec, 2021 2 commits