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  1. 28 Jul, 2023 1 commit
    • Zhaoheng Ni's avatar
      Move TorchAudio-Squim models to Beta (#3512) · b7d2d928
      Zhaoheng Ni authored 
      Summary:
The PR move `SquimObjective` and `SquimSubjective` models and corresponding factory functions and pre-trained pipelines out of prototype and to the core directory. They will be included in the next official release.

Pull Request resolved: https://github.com/pytorch/audio/pull/3512

Reviewed By: mthrok

Differential Revision: D47837434

Pulled By: nateanl

fbshipit-source-id: d0639f29079f7e1afc30f236849e530c8cadffd8
      b7d2d928
  3. 23 Mar, 2023 1 commit
  5. 27 Feb, 2023 1 commit
  7. 15 Jan, 2023 1 commit
    • Zhaoheng Ni's avatar
      Add pre-trained pipelines for XLS-R models (#2978) · 9b7b64e4
      Zhaoheng Ni authored 
      Summary:
The PR adds three `Wav2Vec2Bundle ` pipeline objects for XLS-R models:
- WAV2VEC2_XLSR_300M
- WAV2VEC2_XLSR_1B
- WAV2VEC2_XLSR_2B

All three models use layer normalization in the feature extraction layers, hence `_normalize_waveform` is set to `True`.

Pull Request resolved: https://github.com/pytorch/audio/pull/2978

Reviewed By: hwangjeff

Differential Revision: D42501491

Pulled By: nateanl

fbshipit-source-id: 2429ec880cc14798034843381e458e1b4664dac3
      9b7b64e4
  9. 05 Jan, 2023 1 commit
    • Grigory Sizov's avatar
      Add HiFiGAN bundle (#2921) · 54e5c859
      Grigory Sizov authored 
      Summary:
Closes [T138011314](https://www.internalfb.com/intern/tasks/?t=138011314)
## Description
- Add  bundle `HIFIGAN_GENERATOR_V3_LJSPEECH` to prototypes. The bundle contains pre-trained HiFiGAN generator weights from the [original HiFiGAN publication](https://github.com/jik876/hifi-gan#pretrained-model), converted slightly to fit our model
- Add tests
  - unit tests checking that vocoder and mel-transform implementations in the bundle give the same results as the original ones. Part of the original HiFiGAN code is ported to this repo to enable these tests
  - integration test checking that waveform reconstructed from mel spectrogram by the bundle is close enough to the original
- Add docs

Pull Request resolved: https://github.com/pytorch/audio/pull/2921

Reviewed By: nateanl, mthrok

Differential Revision: D42034761

Pulled By: sgrigory

fbshipit-source-id: 8b0dadeed510b3c9371d6aa2c46ec7d8378f6048
      54e5c859
  11. 09 Dec, 2022 1 commit
  13. 15 Nov, 2022 1 commit
  15. 14 Sep, 2022 1 commit
  17. 13 Sep, 2022 1 commit
  19. 03 Aug, 2022 2 commits
    • Sean Kim's avatar
      Add HDEMUCS_HIGH_MUSDB (#2601) · 6ecc11c2
      Sean Kim authored 
      Summary:
Add new model pretrained weights and tests

Pull Request resolved: https://github.com/pytorch/audio/pull/2601

Reviewed By: carolineechen, nateanl

Differential Revision: D38396673

Pulled By: skim0514

fbshipit-source-id: e06f97d28508543bc18e671344386a947bc870c1
      6ecc11c2
    • bshall's avatar
      An implemenation of the ITU-R BS.1770-4 loudness recommendation (#2472) · 946b180a
      bshall authored 
      Summary:
I took a stab at implementing the ITU-R BS.1770-4 loudness recommendation (closes https://github.com/pytorch/audio/issues/1205). To give some more details:
- I've implemented K-weighting following csteinmetz1 instead of BrechtDeMan since it fit well with torchaudio's already implemented filters (`treble_biquad` and `highpass_biquad`).
- I've added four audio files to test compliance with the recommendation. These are linked in [this pdf](https://www.itu.int/dms_pub/itu-r/opb/rep/R-REP-BS.2217-2-2016-PDF-E.pdf). There are many more test files there but I didn't want to bog down the assets directory with too many files. Let me know if I should add or remove anything.
- I've kept many of the constant internal to the function (e.g. the block duration, overlap, and the absolute threshold gamma). I'm not sure if these should be exposed in the signature.
- I've implemented support for up to 5 channels (following both csteinmetz1 and BrechtDeMan). The recommendation includes weights for up to 24 channels. Is there any convention for how many channels to support?

I hope this is helpful! looking forward to hearing from you.

Pull Request resolved: https://github.com/pytorch/audio/pull/2472

Reviewed By: hwangjeff

Differential Revision: D38389155

Pulled By: carolineechen

fbshipit-source-id: fcc86d864c04ab2bedaa9acd941ebc4478ca6904
      946b180a
  21. 26 Jul, 2022 1 commit
  23. 25 Jul, 2022 1 commit
  25. 22 Jul, 2022 1 commit
    • Zhaoheng Ni's avatar
      Add documents for SourceSeparationBundle (#2559) · 6cee56ab
      Zhaoheng Ni authored 
      Summary:
- Add documentation page for `SourceSeparationBundle` and `CONVTASNET_BASE_LIBRI2MIX`.
- Add citation of Libri2Mix dataset in the bundle documentation.
- url in integration test should use slash instead of `os.path.join` as it will fail on Windows. Change it to f-string.

Pull Request resolved: https://github.com/pytorch/audio/pull/2559

Reviewed By: carolineechen

Differential Revision: D38036116

Pulled By: nateanl

fbshipit-source-id: 736732805191113955badfec3955e2e24e8f4836
      6cee56ab
  27. 21 Jul, 2022 1 commit
    • Zhaoheng Ni's avatar
      Add SourceSeparationBundle to prototype (#2440) · 83362580
      Zhaoheng Ni authored 
      Summary:
- Add SourceSeparationBundle class for source separation pipeline
- Add `CONVTASNET_BASE_LIBRI2MIX` that is trained on Libri2Mix dataset.
- Add integration test with example mixture audio and expected scale-invariant signal-to-distortion ratio (Si-SDR) score. The test computes the Si-SDR score with permutation-invariant training (PIT) criterion for all permutations of sources and use the highest value as the final output. The test verifies if the score is equal to or larger than the expected value.

Pull Request resolved: https://github.com/pytorch/audio/pull/2440

Reviewed By: mthrok

Differential Revision: D37997646

Pulled By: nateanl

fbshipit-source-id: c951bcbbe8b7ed9553cb8793d6dc1ef90d5a29fe
      83362580
  29. 27 Jun, 2022 1 commit
  31. 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
  33. 15 May, 2022 1 commit
    • John Reese's avatar
      [codemod][usort] apply import merging for fbcode (8 of 11) · d62875cc
      John Reese authored 
      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
      d62875cc
  35. 26 Apr, 2022 1 commit
  37. 21 Apr, 2022 1 commit
    • hwangjeff's avatar
      Change underlying implementation of RNN-T hypothesis to tuple (#2339) · 6b242c29
      hwangjeff authored 
      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
      6b242c29
  39. 25 Mar, 2022 1 commit
  41. 22 Mar, 2022 1 commit
    • moto's avatar
      Add download utility specialized for torchaudio (#2283) · 64b98521
      moto authored 
      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
      64b98521
  43. 01 Feb, 2022 1 commit
    • hwangjeff's avatar
      Move ASR features out of prototype (#2187) · aca5591c
      hwangjeff authored 
      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
      aca5591c
  45. 26 Jan, 2022 1 commit
  47. 30 Dec, 2021 1 commit
  49. 23 Dec, 2021 1 commit
  51. 04 Nov, 2021 1 commit
    • moto's avatar
      Consolidate network utils (#1974) · 536e8ac0
      moto authored 
      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.
      536e8ac0
  53. 03 Nov, 2021 1 commit
  55. 02 Nov, 2021 3 commits
  57. 27 Oct, 2021 1 commit
  59. 25 Oct, 2021 1 commit
  61. 22 Oct, 2021 1 commit
  63. 21 Oct, 2021 1 commit
  65. 15 Oct, 2021 2 commits
    • moto's avatar
      Add TTS bundle/pipelines (#1872) · e885204e
      moto authored 
      Future work items:
- length computation of GriffinLim
- better way to make InverseMelScale work in inference_mode
      e885204e
    • moto's avatar
      Move wav2vec2 pretrained models to pipelines module (#1876) · fad855cd
      moto authored 
      - 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
      fad855cd
  67. 08 Oct, 2021 1 commit
  69. 06 Oct, 2021 2 commits