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  1. 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
  3. 04 Mar, 2022 2 commits
    • moto's avatar
      Flush and reset internal state after seek (#2264) · 7e1afc40
      moto authored 
      Summary:
This commit adds the following behavior to `seek` so that `seek`
works after a frame is decoded.

1. Flush the decoder buffer.
2. Recreate filter graphs (so that internal state is re-initialized)
3. Discard the buffered tensor. (decoded chunks)

Also it disallows negative values for seek timestamp.

Pull Request resolved: https://github.com/pytorch/audio/pull/2264

Reviewed By: carolineechen

Differential Revision: D34497826

Pulled By: mthrok

fbshipit-source-id: 8b9a5bf160dfeb15f5cced3eed2288c33e2eb35d
      7e1afc40
    • moto's avatar
      Make Streamer fail if an invalid option is provided (#2263) · 04875eef
      moto authored 
      Summary:
`torchaudio.prototype.io.Streamer` class takes context dependant options
as `option` argument in the form of mappings of strings.

Currently there is no check if the provided options were valid for
the given input.

This commit adds the check and raise an error if an invalid erro is given.

This is analogous to `ffmpeg` command error handling.

```
$ ffmpeg -foo
...
Unrecognized option 'foo'.
```

Pull Request resolved: https://github.com/pytorch/audio/pull/2263

Reviewed By: hwangjeff

Differential Revision: D34495111

Pulled By: mthrok

fbshipit-source-id: cd068de0dc1d1273bdd5d40312c3faccb47b253f
      04875eef
  5. 26 Feb, 2022 2 commits
  7. 25 Feb, 2022 5 commits
  9. 24 Feb, 2022 1 commit
  11. 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
  13. 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
  15. 15 Feb, 2022 1 commit
  17. 11 Feb, 2022 2 commits
  19. 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
  21. 02 Feb, 2022 1 commit
  23. 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
  25. 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
  27. 26 Jan, 2022 3 commits
  29. 21 Jan, 2022 1 commit
  31. 20 Jan, 2022 1 commit
  33. 05 Jan, 2022 1 commit
  35. 30 Dec, 2021 2 commits
  37. 29 Dec, 2021 3 commits
  39. 23 Dec, 2021 3 commits
  41. 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