1. 04 Sep, 2023 1 commit
  2. 15 Aug, 2023 1 commit
    • moto's avatar
      [BC-breaking] Update pre-built ffmpeg4 to 4.4.4 (#3561) · bf07ea6b
      moto authored
      Summary:
      In https://github.com/pytorch/audio/pull/3460, we switched the build process for FFmpeg extension.
      Since it is complicated to install FFmpeg in some environments, at build time, pre-built binaries and its headers
      are downloaded and used as a scaffolding for torchaudio build.
      
      Now even though we did not change any code or FFmpeg version, it turned out that this causes segmentation
      fault on Ubuntu when using system Python and FFmpeg 4.4 installed via aptitude.
      While investigating the issue, I swapped the said pre-built FFmpeg scaffolding with FFmpeg 4.4 from aptitude,
      and the segmentation fault did not happen. This indicates that it is binary compatibility issue.
      
      Before https://github.com/pytorch/audio/issues/3460, each binary build job was building FFmpeg 4.1.8 using the same compiler used to build torchaudio,
      but after https://github.com/pytorch/audio/issues/3460 the environments to build FFmpeg 4.1.8 and torchaudio are different. My hypothesis is that
      this difference is causing some ABI incompatibility when linking against FFmpeg 4.4. (Also, I don't remember well,
      but I read somewhere that 4.4 has a different ABI)
      
      Through experiments, it turned out upgrading the pre-built FFmpeg scaffolding to 4.4 resolves this.
      So this commit upgrade the pre-built FFmpeg 4 to 4.4.
      The potential (yet unconfirmed) downside is that torchaudio will no longer work with 4.1, 4.2, and 4.3.
      Since FFmpeg 4.4 is what Ubuntu 20.04 and 22.04 support by default, and Google Colab is also on 20.04,
      I think it is more important to support 4.4.
      
      Therefore we drop the support for 4.1-4.3 from normal build (and official distributions). Those who wish to
      use 4.1-4.3 can build torchaudio from source by linking to specific FFmpeg.
      
      Pull Request resolved: https://github.com/pytorch/audio/pull/3561
      
      Reviewed By: hwangjeff
      
      Differential Revision: D48340201
      
      Pulled By: mthrok
      
      fbshipit-source-id: 7ece82910f290c7cf83f58311c4cf6a384e8795e
      bf07ea6b
  3. 15 Jul, 2023 1 commit
  4. 26 May, 2023 1 commit
  5. 16 May, 2023 1 commit
  6. 13 Oct, 2022 1 commit
  7. 07 Oct, 2022 1 commit
  8. 05 Oct, 2022 1 commit
  9. 18 Aug, 2022 1 commit
  10. 13 May, 2022 1 commit
    • moto's avatar
      Move Streamer API out of prototype (#2378) · 72b712a1
      moto authored
      Summary:
      This commit moves the Streaming API out of prototype module.
      
      * The related classes are renamed as following
      
        - `Streamer` -> `StreamReader`.
        - `SourceStream` -> `StreamReaderSourceStream`
        - `SourceAudioStream` -> `StreamReaderSourceAudioStream`
        - `SourceVideoStream` -> `StreamReaderSourceVideoStream`
        - `OutputStream` -> `StreamReaderOutputStream`
      
      This change is preemptive measurement for the possibility to add
      `StreamWriter` API.
      
      * Replace BUILD_FFMPEG build arg with USE_FFMPEG
      
      We are not building FFmpeg, so USE_FFMPEG is more appropriate
      
       ---
      
      After https://github.com/pytorch/audio/issues/2377
      
      Remaining TODOs: (different PRs)
      - [ ] Introduce `is_ffmpeg_binding_available` function.
      - [ ] Refactor C++ code:
         - Rename `Streamer` to `StreamReader`.
         - Rename `streamer.[h|cpp]` to `stream_reader.[h|cpp]`.
         - Rename `prototype.cpp` to `stream_reader_binding.cpp`.
         - Introduce `stream_reader` directory.
      - [x] Enable FFmpeg in smoke test (https://github.com/pytorch/audio/issues/2381)
      
      Pull Request resolved: https://github.com/pytorch/audio/pull/2378
      
      Reviewed By: carolineechen
      
      Differential Revision: D36359299
      
      Pulled By: mthrok
      
      fbshipit-source-id: 6a57b702996af871e577fb7addbf3522081c1328
      72b712a1
  11. 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
  12. 13 Apr, 2022 1 commit
    • hwangjeff's avatar
      Add nightly build installation code snippet to prototype feature tutorials (#2325) · fb51cecc
      hwangjeff authored
      Summary:
      Tutorial notebooks that leverage TorchAudio prototype features don't run as-is on Google Colab due to its runtime's not having nightly builds pre-installed. To make it easier for users to run said notebooks in Colab, this PR adds a code block that installs nightly Pytorch and TorchAudio builds as a comment that users can copy and run locally.
      
      Pull Request resolved: https://github.com/pytorch/audio/pull/2325
      
      Reviewed By: xiaohui-zhang
      
      Differential Revision: D35597753
      
      Pulled By: hwangjeff
      
      fbshipit-source-id: 59914e492ad72e31c0136a48cd88d697e8ea5f6c
      fb51cecc
  13. 10 Mar, 2022 1 commit
  14. 26 Feb, 2022 1 commit
    • moto's avatar
      Improve device streaming (#2202) · 365313ed
      moto authored
      Summary:
      This commit adds tutorial for device ASR, and update API for device streaming.
      
      The changes for the interface are
      1. Add `timeout` and `backoff` parameters to `process_packet` and `stream` methods.
      2. Move `fill_buffer` method to private.
      
      When dealing with device stream, there are situations where the device buffer is not
      ready and the system returns `EAGAIN`. In such case, the previous implementation of
      `process_packet` method raised an exception in Python layer , but for device ASR,
      this is inefficient. A better approach is to retry within C++ layer in blocking manner.
      The new `timeout` parameter serves this purpose.
      
      Pull Request resolved: https://github.com/pytorch/audio/pull/2202
      
      Reviewed By: nateanl
      
      Differential Revision: D34475829
      
      Pulled By: mthrok
      
      fbshipit-source-id: bb6d0b125d800f87d189db40815af06fbd4cab59
      365313ed