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  1. 25 Feb, 2022 4 commits
  3. 24 Feb, 2022 1 commit
  5. 17 Feb, 2022 2 commits
    • Zhaoheng Ni's avatar
      Refactor batch consistency test in functional (#2245) · 9cf59e75
      Zhaoheng Ni authored 
      Summary:
In batch_consistency tests, the `assert_batch_consistency` method only accepts single Tensor, which is not applicable to some methods. For example, `lfilter` and `filtfilt` requires three Tensors as the arguments, hence they don't follow `assert_batch_consistency` in the tests.
This PR refactors the test to accept a tuple of Tensors which have `batch` dimension. For the other arguments like `int` or `str`, they are given as `*args` after the tuple.

Pull Request resolved: https://github.com/pytorch/audio/pull/2245

Reviewed By: mthrok

Differential Revision: D34273035

Pulled By: nateanl

fbshipit-source-id: 0096b4f062fb4e983818e5374bed6efc7b15b056
      9cf59e75
    • Zhaoheng Ni's avatar
      Add unit tests for PyTorch Lightning modules of emformer_rnnt recipes (#2240) · b5d77b15
      Zhaoheng Ni authored 
      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
      b5d77b15
  7. 16 Feb, 2022 2 commits
    • Zhaoheng Ni's avatar
      Refactor torchscript consistency test in functional (#2246) · 87d79889
      Zhaoheng Ni authored 
      Summary:
In torchscript_consistency tests, the `func` in each test method only accepts one `tensor` as the argument, for the other arguments of `F.xyz` method, they need to be defined inside the `func`. If there is no `Tensor` argument in `F.xzy`, the tests use a `dummy` tensor which is not used anywhere. In this PR, we refactor ``_assert_consistency`` and ``_assert_consistency_complex`` to accept a tuple of inputs instead of just one `tensor`.

Pull Request resolved: https://github.com/pytorch/audio/pull/2246

Reviewed By: carolineechen

Differential Revision: D34273057

Pulled By: nateanl

fbshipit-source-id: a3900edb3b2c58638e513e1490279d771ebc3d0b
      87d79889
    • Zhaoheng Ni's avatar
      Add complex dtype support in functional autograd test (#2244) · eeba91dc
      Zhaoheng Ni authored 
      Summary:
In autograd tests, to guarantee the precision, the dtype of Tensors are converted to `torch.float64` if they are real. However, the complex dtype is not considered. This PR adds `self.complex_dtype` support to the inputs.

Pull Request resolved: https://github.com/pytorch/audio/pull/2244

Reviewed By: mthrok

Differential Revision: D34272998

Pulled By: nateanl

fbshipit-source-id: e8698a74d7b8d99ee0fcb5f5cb5f2ffc8c80b9b5
      eeba91dc
  9. 15 Feb, 2022 1 commit
  11. 11 Feb, 2022 2 commits
  13. 09 Feb, 2022 2 commits
    • hwangjeff's avatar
      Clean up Emformer (#2207) · 87d7694d
      hwangjeff authored 
      Summary:
- Make `segment_length` a required argument rather than optional argument to force users to consciously choose input segment lengths for their use cases.
- Clarify expected input shapes in API documentation.
- Adjust `infer` tests to reflect expected usage.
- Add assertion for input shape for `infer`.

Pull Request resolved: https://github.com/pytorch/audio/pull/2207

Reviewed By: mthrok

Differential Revision: D34101205

Pulled By: hwangjeff

fbshipit-source-id: 1d1233d5edee5818d4669b4e47d44559e7ebb304
      87d7694d
    • hwangjeff's avatar
      Fix librosa calls (#2208) · e5d567c9
      hwangjeff authored 
      Summary:
Yesterday's release of librosa 0.9.0 made args keyword-only and changed default padding from "reflect" to "zero" for some functions. This PR adjusts callsites in our tutorials and tests accordingly.

Pull Request resolved: https://github.com/pytorch/audio/pull/2208

Reviewed By: mthrok

Differential Revision: D34099793

Pulled By: hwangjeff

fbshipit-source-id: 4e2642cdda8aae6d0a928befaf1bbb3873d229bc
      e5d567c9
  15. 02 Feb, 2022 1 commit
  17. 01 Feb, 2022 2 commits
    • 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
    • Caroline Chen's avatar
      Add CTC decoder timesteps (#2184) · d43ce015
      Caroline Chen authored 
      Summary:
add timesteps field to CTC decoder hypotheses, corresponding to the time step of occurrences of non-blank tokens

Pull Request resolved: https://github.com/pytorch/audio/pull/2184

Reviewed By: mthrok

Differential Revision: D33905530

Pulled By: carolineechen

fbshipit-source-id: c575d25655fcf252754ee3c2447949a4c059461a
      d43ce015
  19. 27 Jan, 2022 2 commits
    • Caroline Chen's avatar
      Add no lm support for CTC decoder (#2174) · 4c3fa875
      Caroline Chen authored 
      Summary:
Add support for CTC lexicon decoder without LM support by adding a non language model `ZeroLM` that returns score 0 for everything. Generalize the decoder class/API a bit to support this, adding it as an option for the kenlm decoder at the moment (will likely be separated out from kenlm when adding support for other kinds of LMs in the future)

Pull Request resolved: https://github.com/pytorch/audio/pull/2174

Reviewed By: hwangjeff, nateanl

Differential Revision: D33798674

Pulled By: carolineechen

fbshipit-source-id: ef8265f1d046011b143597b3b7c691566b08dcde
      4c3fa875
    • moto's avatar
      Add `is_ffmpeg_available` in test (#2170) · 39fe9df6
      moto authored 
      Summary:
Part of https://github.com/pytorch/audio/issues/2164.
To make the tests introduced in https://github.com/pytorch/audio/issues/2164 skippable if ffmpeg features are not available,
this commit adds `is_ffmpeg_available`.

The availability of the features depend on two factors;
1. If it was enabled at build.
2. If the ffmpeg libraries are found at runtime.

A simple way (for OSS workflow) to detect these is simply checking if
`libtorchaudio_ffmpeg` presents and can be loaded without a failure.

To facilitate this, this commit changes the
`torchaudio._extension._load_lib` to return boolean result.

Pull Request resolved: https://github.com/pytorch/audio/pull/2170

Reviewed By: carolineechen

Differential Revision: D33797695

Pulled By: mthrok

fbshipit-source-id: 85e767fc06350b8f99de255bc965b8c92b8cfe97
      39fe9df6
  21. 26 Jan, 2022 2 commits
  23. 21 Jan, 2022 1 commit
  25. 20 Jan, 2022 1 commit
  27. 05 Jan, 2022 1 commit
  29. 30 Dec, 2021 2 commits
  31. 29 Dec, 2021 3 commits
  33. 23 Dec, 2021 3 commits
  35. 21 Dec, 2021 1 commit
    • moto's avatar
      Fix load behavior for 24-bit input (#2084) · 4554d242
      moto authored 
      Summary:
## bug description

When a 24 bits-par-sample audio is loaded via file-like object,
the loaded Tensor is wrong. It was fine if the audio is loaded
from local file.

## The cause of the bug

The core of the sox's decoding mechanism is `sox_read` function,
one of which parameter is the maximum number of samples to decode
from the given buffer.

https://fossies.org/dox/sox-14.4.2/formats_8c.html#a2a4f0194a0f919d4f38c57b81aa2c06f)]

The `sox_read` function is called in what is called `drain` effect,
callback and this callback receives output buffer and its size in
byte. The previous implementation passed this size value as
the argument of `sox_read` for the maximum number of samples to
read. Since buffer size is larger than the number of samples fit in
the buffer, `sox_read` function always consumed the entire
buffer. (This behavior is not wrong except when the input is
24 bits-per-sample and file-like object.)

When the input is read from file-like object, inside of drain
callback, new data are fetched via Python's `read` method and
loaded on fixed-size memory region. The size of this memory region
can be adjusted via `torchaudio.utils.sox_utils.set_buffer_size`,
but the default value is 8096.

If the input format is 24 bits-per-sample, the end of memory region
does not necessarily correspond to the end of a valid sample.
When `sox_read` consumes all the data in the buffer region, the data
at the end introduces some unexpected values.
This causes the aforementioned bug

## Fix

Pass proper (better estimated) maximum number of samples decodable to
`sox_read`.

Pull Request resolved: https://github.com/pytorch/audio/pull/2084

Reviewed By: carolineechen

Differential Revision: D33236947

Pulled By: mthrok

fbshipit-source-id: 171d9b7945f81db54f98362a68b20f2f95bb11a4
      4554d242
  37. 30 Nov, 2021 1 commit
    • hwangjeff's avatar
      Revise Griffin-Lim transform test to reduce execution time (#2037) · 96b1fa72
      hwangjeff authored 
      Summary:
Our Griffin-Lim autograd tests take a long time to run. This PR adjusts some parameters to shorten the run time.

For one of the four tests:
Before:
```
test/torchaudio_unittest/transforms/autograd_cpu_test.py . [100%]

======================== 1 passed in 517.35s (0:08:37) =========================
```

After:
```
test/torchaudio_unittest/transforms/autograd_cpu_test.py . [100%]

======================== 1 passed in 104.59s (0:01:44) =========================
```

Pull Request resolved: https://github.com/pytorch/audio/pull/2037

Reviewed By: mthrok

Differential Revision: D32726213

Pulled By: hwangjeff

fbshipit-source-id: c785323ab380aea4b63fb1683b557c8ae842f54e
      96b1fa72
  39. 24 Nov, 2021 1 commit
    • hwangjeff's avatar
      Add RNN-T beam search decoder (#2028) · 60a85b50
      hwangjeff authored 
      Summary:
Adds beam search decoder for RNN-T implementation ``torchaudio.prototype.RNNT`` that is TorchScript-able and supports both streaming and non-streaming inference.

Pull Request resolved: https://github.com/pytorch/audio/pull/2028

Reviewed By: mthrok

Differential Revision: D32627919

Pulled By: hwangjeff

fbshipit-source-id: aab99e346d6514a3207a9fb69d4b42978b4cdbbd
      60a85b50
  41. 23 Nov, 2021 1 commit
    • moto's avatar
      Temporarily skip threadpool test (#2025) · 05ae795a
      moto authored 
      Summary:
The sox_effects test in `concurrent.future.ThreadPoolExecutor` started failing since couple of days. While investigate this, skipping the test.

Pull Request resolved: https://github.com/pytorch/audio/pull/2025

Reviewed By: nateanl

Differential Revision: D32615933

Pulled By: mthrok

fbshipit-source-id: 4f7301c0d3c0d11f687011e42e06d9c87ce4197f
      05ae795a
  43. 22 Nov, 2021 2 commits
    • Zhaoheng Ni's avatar
      Relax dtype for MVDR (#2024) · 392a03c8
      Zhaoheng Ni authored 
      Summary:
Allow users to use `torch.cfloat` dtype input for MVDR module. It internally convert the spectrogram into `torch.cdouble` and output the tensor with the original dtype of the spectrogram.

Pull Request resolved: https://github.com/pytorch/audio/pull/2024

Reviewed By: carolineechen

Differential Revision: D32594051

Pulled By: nateanl

fbshipit-source-id: e32609ccdc881b36300d579c90daba41c9234b46
      392a03c8
    • Zhaoheng Ni's avatar
      Improve MVDR stability (#2004) · fb2f9538
      Zhaoheng Ni authored 
      Summary:
Division first, multiplication second. This helps avoid the value overflow issue. It also helps the ``stv_evd`` solution pass the gradient check.

Pull Request resolved: https://github.com/pytorch/audio/pull/2004

Reviewed By: mthrok

Differential Revision: D32539827

Pulled By: nateanl

fbshipit-source-id: 70a386608324bb6e1b1c7238c78d403698590f22
      fb2f9538
  45. 18 Nov, 2021 2 commits