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  1. 23 Dec, 2021 4 commits
  3. 22 Dec, 2021 2 commits
  5. 21 Dec, 2021 3 commits
    • Moto Hira's avatar
      Clean up CTC decoder bynding code (#2092) · 4c2edd21
      Moto Hira authored 
      Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2092

Reviewed By: carolineechen

Differential Revision: D33169110

fbshipit-source-id: e422ad93efe50b91f1ac5d572dc82768c1000c05
      4c2edd21
    • moto's avatar
      Update audio augmentation tutorial (#2082) · 3a03d8c0
      moto authored 
      Summary:
1. Reorder Audio display so that audios are playable from browser in doc
2. Add link to function documentations

https://470342-90321822-gh.circle-artifacts.com/0/docs/tutorials/audio_data_augmentation_tutorial.html

Pull Request resolved: https://github.com/pytorch/audio/pull/2082

Reviewed By: carolineechen

Differential Revision: D33227725

Pulled By: mthrok

fbshipit-source-id: c7ee360b6f9b84c8e0a9b72193b98487d03b57ab
      3a03d8c0
    • 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
  7. 20 Dec, 2021 3 commits
  9. 18 Dec, 2021 1 commit
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  13. 15 Dec, 2021 1 commit
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  25. 03 Dec, 2021 5 commits
  27. 02 Dec, 2021 1 commit
    • moto's avatar
      Refactor the library loading mechanism (#2038) · 9114e636
      moto authored 
      Summary:
(This is a part of refactor series, followed up by https://github.com/pytorch/audio/issues/2039 and https://github.com/pytorch/audio/issues/2040.
The goal is to make it easy to add a new library artifact alongside with `libtorchudio`, as in https://github.com/pytorch/audio/pull/2048/commits/4ced990849e60f6d19e87ae22819b04d1726648e https://github.com/pytorch/audio/issues/2048 .)

We plan to add prototype/beta third party library integrations,
which could be unstable. (segfault, missing dynamic library dependencies etc...)

If we add such integrations into the existing libtorchaudio,
in the worst case, it will prevent users from just `import torchaudio`.

Instead, we would like to separate the prototype/beta integrations
into separate libraries, so that such issues would not impact all users but
users who attempt to use these prototytpe/beta features.

Say, a prototype feature `foo` is added in `torchaudio.prototype.foo`.
The following initialization procedure will achieve the above mechanism.

1. Place the library file `libtorchaudio_foo` in `torchaudio/lib`.
2. In `torchaudio.prototype.foo.__init__.py`, load the `libtorchaudio_foo`.

Note:
The approach will be slightly different for fbcode, because of how buck deploys
C++ libraries and standardized environment, but the code change here is still
applicable.

Pull Request resolved: https://github.com/pytorch/audio/pull/2038

Reviewed By: carolineechen, nateanl

Differential Revision: D32682900

Pulled By: mthrok

fbshipit-source-id: 0f402a92a366fba8c2894a0fe01f47f8cdd51376
      9114e636
  29. 30 Nov, 2021 2 commits
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  35. 22 Nov, 2021 2 commits