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    • Caroline Chen's avatar
      Enable log probs input for rnnt loss (#2798) · ca478823
      Caroline Chen authored 
      Summary:
Add `fused_log_softmax` argument (default/current behavior = True) to rnnt loss.

If setting it to `False`, call `log_softmax` on the logits prior to passing it in to the rnnt loss function.

The following should produce the same output:
```
rnnt_loss(logits, targets, logit_lengths, target_lengths, fused_log_softmax=True)
```

```
log_probs = torch.nn.functional.log_softmax(logits, dim=-1)
rnnt_loss(log_probs, targets, logit_lengths, target_lengths, fused_log_softmax=False)
```

testing -- unit tests + get same results on the conformer rnnt recipe

Pull Request resolved: https://github.com/pytorch/audio/pull/2798

Reviewed By: xiaohui-zhang

Differential Revision: D41083523

Pulled By: carolineechen

fbshipit-source-id: e15442ceed1f461bbf06b724aa0561ff8827ad61
      ca478823
    • hwangjeff's avatar
      Add convolution transforms (#2811) · 2d99fee2
      hwangjeff authored 
      Summary:
Adds `torch.nn.Module`-based implementations for convolution and FFT convolution.

Pull Request resolved: https://github.com/pytorch/audio/pull/2811

Reviewed By: carolineechen

Differential Revision: D40881937

Pulled By: hwangjeff

fbshipit-source-id: bfe8969e6178ad4f58981efd4b2720ac006be8de
      2d99fee2
  35. 04 Nov, 2022 1 commit
  37. 31 Oct, 2022 1 commit
  39. 28 Oct, 2022 1 commit
  41. 26 Oct, 2022 1 commit
    • hwangjeff's avatar
      Deprecate 'onesided' init param for MelSpectrogram (#2797) · 546e699a
      hwangjeff authored 
      Summary:
Initializer parameter `onesided` isn't relevant to `MelSpectrogram` — it should always be `True`. In fact, the module already assumes `onesided == True` in the filterbank it generates and fails in its forward pass when `onesided == False`. Accordingly, this PR makes param `onesided` optional and adds a deprecation warning that's fired when the param is provided.

Pull Request resolved: https://github.com/pytorch/audio/pull/2797

Reviewed By: carolineechen, xiaohui-zhang

Differential Revision: D40731238

Pulled By: hwangjeff

fbshipit-source-id: 6eea8eb9d4a85a805162e03ad91682a1946f92cd
      546e699a
  43. 25 Oct, 2022 1 commit
    • moto's avatar
      Fix issue with the missing video frame in StreamWriter (#2789) · 17a2b93b
      moto authored 
      Summary:
Addresses https://github.com/pytorch/audio/issues/2790.

Previously AVPacket objects had duration==0.

`av_interleaved_write_frame` function was inferring the duration of packets by
comparing them against the next ones but It could not infer the duration of
the last packet, as there is no subsequent frame, thus was omitting it from the final data.

This commit fixes it by explicitly setting packet duration = 1 (one frame)
only for video. (audio AVPacket contains multiple samples, so it's different.
To ensure the correctness for audio, the tests were added.)

Pull Request resolved: https://github.com/pytorch/audio/pull/2789

Reviewed By: xiaohui-zhang

Differential Revision: D40627439

Pulled By: mthrok

fbshipit-source-id: 4d0d827bff518c017b115445e03bdf0bf1e68320
      17a2b93b
  45. 19 Oct, 2022 2 commits
  47. 12 Oct, 2022 1 commit
    • Caroline Chen's avatar
      Skip hubert xlarge torchscript test (#2758) · c2ea6898
      Caroline Chen authored 
      Summary:
a couple of circleci unittests are failing during hubert xlarge torchscript test, which has been known to fail on Windows in the past (#65776). this PR disables this test on circleci

cc atalman

Pull Request resolved: https://github.com/pytorch/audio/pull/2758

Reviewed By: mthrok

Differential Revision: D40290535

Pulled By: carolineechen

fbshipit-source-id: 5c5fb43434a517b6c439a8cb8e853015d1550a57
      c2ea6898
  49. 11 Oct, 2022 1 commit
  51. 10 Oct, 2022 1 commit
    • Zhaoheng Ni's avatar
      Add unit test for LibriMix dataset (#2659) · c5b8e585
      Zhaoheng Ni authored 
      Summary:
Besides the unit test, the PR also addresses these issues:
- The original `LibriMix` dataset only supports "min" mode, which means the audio length is the minimum of all clean sources. It is default for source separation task. Users may also want to use "max" mode which allows for end-to-end separation and recognition. The PR adds ``mode`` argument to let users decide which dataset they want to use.
- If the task is ``"enh_both"``, the target is the audios in ``mix_clean`` instead of separate clean sources. The PR fixes it to use ``mix_clean`` as target.

Pull Request resolved: https://github.com/pytorch/audio/pull/2659

Reviewed By: carolineechen

Differential Revision: D40229227

Pulled By: nateanl

fbshipit-source-id: fc07e0d88a245e1367656d3767cf98168a799235
      c5b8e585
  53. 09 Oct, 2022 1 commit
  55. 07 Oct, 2022 1 commit
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  61. 13 Sep, 2022 1 commit