1. 10 May, 2023 1 commit
  2. 29 Apr, 2023 1 commit
  3. 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
  4. 11 Feb, 2023 1 commit
  5. 07 Feb, 2023 1 commit
  6. 01 Feb, 2023 1 commit
  7. 30 Dec, 2022 1 commit
  8. 17 Dec, 2022 1 commit
  9. 07 Dec, 2022 1 commit
  10. 29 Nov, 2022 1 commit
  11. 28 Nov, 2022 1 commit
  12. 15 Nov, 2022 1 commit
  13. 08 Nov, 2022 1 commit
  14. 02 Nov, 2022 1 commit
  15. 28 Oct, 2022 1 commit
  16. 23 Sep, 2022 1 commit
  17. 15 Sep, 2022 1 commit
  18. 15 Aug, 2022 1 commit
  19. 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
  20. 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
  21. 08 Jun, 2022 1 commit
  22. 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
  23. 20 May, 2022 1 commit
  24. 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
  25. 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
  26. 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
  27. 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
  28. 04 Feb, 2022 1 commit
  29. 03 Feb, 2022 1 commit
  30. 02 Feb, 2022 1 commit
  31. 01 Feb, 2022 1 commit
  32. 29 Dec, 2021 2 commits
  33. 28 Dec, 2021 1 commit
  34. 05 Nov, 2021 4 commits
  35. 04 Nov, 2021 2 commits