- 04 Jun, 2022 1 commit
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Caroline Chen authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2443 Reviewed By: nateanl Differential Revision: D36909822 Pulled By: carolineechen fbshipit-source-id: ef3ab2345e7a4666cf29dd02c83d03504e8aa62c
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- 03 Jun, 2022 5 commits
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moto authored
Summary: - Adopt `torchaudio.utils.download_asset` to simplify asset management. - Break down the first section about helper functions. - Reduce the number of helper functions https://output.circle-artifacts.com/output/job/d7dd1b93-6dfe-46da-a080-109bfdc63881/artifacts/0/docs/tutorials/audio_data_augmentation_tutorial.html Pull Request resolved: https://github.com/pytorch/audio/pull/2388 Reviewed By: carolineechen Differential Revision: D36404405 Pulled By: mthrok fbshipit-source-id: f460ed810519797fce6e2fa7baaee110bddd1d06
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moto authored
Summary: - Replace mis-use of plot_specgram with plot_sweep, and remove plot_specgram - Move `benchmark_resample` to later section https://output.circle-artifacts.com/output/job/9f7af187-777d-4d75-840f-2630a36295b7/artifacts/0/docs/tutorials/audio_resampling_tutorial.html Pull Request resolved: https://github.com/pytorch/audio/pull/2386 Reviewed By: carolineechen Differential Revision: D36404403 Pulled By: mthrok fbshipit-source-id: f9df8453e3f531bdc4549b0134e5dbba90653bf7
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moto authored
Summary: - Adopt torchaudio.utils.download_asset to simplify asset management. - Break down the first section about helper functions. - Reduce the number of helper functions Pull Request resolved: https://github.com/pytorch/audio/pull/2391 Reviewed By: carolineechen, nateanl Differential Revision: D36885626 Pulled By: mthrok fbshipit-source-id: 1306f22ab70ab1e7f74ed7e43bf43150015448b6
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Sean Kim authored
Summary: For test files where applicable, removed manual seeds where applicable. Refactoring https://github.com/pytorch/audio/issues/2267 Pull Request resolved: https://github.com/pytorch/audio/pull/2436 Reviewed By: carolineechen Differential Revision: D36896854 Pulled By: skim0514 fbshipit-source-id: 7b4dd8a8dbfbef271f5cc56564dc83a760407e6c
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Andrey Talman authored
Summary: Refactor M1 logic These improvement introduced in following PR: https://github.com/pytorch/vision/pull/6117 Pull Request resolved: https://github.com/pytorch/audio/pull/2438 Reviewed By: nateanl Differential Revision: D36896028 Pulled By: atalman fbshipit-source-id: 2ce360bfa78b2a7c77d5d4db800d487d171831a9
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- 02 Jun, 2022 5 commits
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Andrey Talman authored
Summary: Retrieve version from version.txt These improvement introduced in following PR: https://github.com/pytorch/vision/pull/6117 In addition to this we add version.txt file to help us manage torchaudio version Pull Request resolved: https://github.com/pytorch/audio/pull/2434 Reviewed By: mthrok Differential Revision: D36867886 Pulled By: atalman fbshipit-source-id: 14b6d653e46489d8db1c5ae2016a8202c632861e
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Caroline Chen authored
Summary: update QUESST14 getitem to include docstrings and additionally return sample rate Pull Request resolved: https://github.com/pytorch/audio/pull/2435 Reviewed By: nateanl Differential Revision: D36864254 Pulled By: carolineechen fbshipit-source-id: 9e68bbc5de27ad2f32f6b298414103c4f6784801
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moto authored
Summary: Remove the code related to libmad, which had been disabled in https://github.com/pytorch/audio/issues/2354 In https://github.com/pytorch/audio/issues/2419, we mp3 decoding to ffmpeg. But CI tests were still using libmad. This commit completely removes libmad from torchaudio. This is BC-breaking change as `apply_sox_effects_file` function cannot handle MP3, and it cannot fallback to ffmpeg. The workaround for this is to use `torchaudio.load` then `apply_sox_effects_tensor`. Pull Request resolved: https://github.com/pytorch/audio/pull/2428 Reviewed By: carolineechen Differential Revision: D36851805 Pulled By: mthrok fbshipit-source-id: f98795c59a1ac61cef511f2bbeac37f7c3c69d55
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Zhaoheng Ni authored
Summary: - Use `download_asset` to download audios. - Replace `MVDR` module with new-added `SoudenMVDR` and `RTFMVDR` modules. - Benchmark performances of `F.rtf_evd` and `F.rtf_power` for RTF computation. - Visualize the spectrograms and masks. Pull Request resolved: https://github.com/pytorch/audio/pull/2398 Reviewed By: carolineechen Differential Revision: D36549402 Pulled By: nateanl fbshipit-source-id: dfd6754e6c33246e6991ccc51c4603b12502a1b5
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moto authored
Summary: This commit add fallback mechanism to `info` and `load` functions of sox_io backend. If torchaudio is compiled to use FFmpeg, and runtime dependencies are properly loaded, in case `info` and `load` fail, it fallback to FFmpeg-based implementation. BC-breaking changes: - FFmpeg does not report the number of frames for MP3, this is because MP3 does not store the information of the number of frames. It can be estimated from the audio duration and sample rate, but it might be inaccurate, so we keep it 0. Depends on - https://github.com/pytorch/audio/issues/2416 - https://github.com/pytorch/audio/issues/2417 - https://github.com/pytorch/audio/issues/2418 - https://github.com/pytorch/audio/issues/2423 - https://github.com/pytorch/audio/issues/2427 Pull Request resolved: https://github.com/pytorch/audio/pull/2419 Reviewed By: carolineechen Differential Revision: D36740306 Pulled By: mthrok fbshipit-source-id: 9e2ad095b8b39e41404970de0d8d9b5aaa856c97
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- 01 Jun, 2022 8 commits
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Sean Kim authored
Summary: Checks download flag and raises error when dataset is missing given download flag exists. Unit tested manually. edit: Changed path to check as well as comment that is returned. Pull Request resolved: https://github.com/pytorch/audio/pull/2430 Reviewed By: carolineechen Differential Revision: D36815729 Pulled By: skim0514 fbshipit-source-id: f062db7919271665b88ec9754d85cfa83b4f6fa3
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moto authored
Summary: A couple of weeks ago we started to see OpenMP not found error on macOS CI. From https://github.com/pytorch/audio/issues/2404, we install OpenMP from brew, and build passes, but unit tests are seg-faulting ever since. https://app.circleci.com/pipelines/github/pytorch/audio/10825/workflows/c0ecae99-d409-4df2-ab91-9bcb126c309d/jobs/671518 The failing test uses `torchaudio.functional.filitfilt`, which uses [OpenMP for parallel execution](https://github.com/pytorch/audio/blob/6057d3cf1c2f3a4c5072a3853a021bb8b4ce61f7/torchaudio/csrc/lfilter.cpp#L20). This commit reverts https://github.com/pytorch/audio/issues/2404 and disables OpenMP for macOS builds and tests. Pull Request resolved: https://github.com/pytorch/audio/pull/2431 Reviewed By: atalman Differential Revision: D36819141 Pulled By: mthrok fbshipit-source-id: 824300866a55f8b029d21649dc96cd80ae2ff697
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moto authored
Summary: * Update error messages * Update audio stream tests Pull Request resolved: https://github.com/pytorch/audio/pull/2429 Reviewed By: carolineechen, nateanl Differential Revision: D36812769 Pulled By: mthrok fbshipit-source-id: 7a51d0c4dbae558010d2e59412333e4a7f00d318
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Sean Kim authored
Summary: Bringing in move seed commit from previous open commit https://github.com/pytorch/audio/issues/2267. Organizes seed to utils. Pull Request resolved: https://github.com/pytorch/audio/pull/2425 Reviewed By: carolineechen, nateanl Differential Revision: D36787599 Pulled By: skim0514 fbshipit-source-id: 37a0d632d13d4336a830c4b98bdb04828ed88c20
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Caroline Chen authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2426 Reviewed By: nateanl Differential Revision: D36791423 Pulled By: carolineechen fbshipit-source-id: e011147a716c940755032b8c68f5717d11fc91bf
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Zhaoheng Ni authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2411 Reviewed By: carolineechen Differential Revision: D36663904 Pulled By: nateanl fbshipit-source-id: c6a7dd530c9cfbb58b7121ebe02db6ae293cc2d0
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Caroline Chen authored
Summary: Move CTC beam search decoder out of prototype to new `torchaudio.models.decoder` module. hwangjeff mthrok any thoughts on the new module + naming, and if we should move rnnt beam search here as well?? Pull Request resolved: https://github.com/pytorch/audio/pull/2410 Reviewed By: mthrok Differential Revision: D36784521 Pulled By: carolineechen fbshipit-source-id: a2ec52f86bba66e03327a9af0c5df8bbefcd67ed
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moto authored
Summary: Extract from https://github.com/pytorch/audio/issues/2419. Move the `FileObj` definition to dedicated file, so that it can be reused from files other than StreamReader. Pull Request resolved: https://github.com/pytorch/audio/pull/2427 Reviewed By: carolineechen Differential Revision: D36794367 Pulled By: mthrok fbshipit-source-id: 999658f3f4d833566d933c9223e7a5d49d300574
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- 31 May, 2022 2 commits
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moto authored
Summary: Extracted from https://github.com/pytorch/audio/issues/2419. Move the failure of sox_io from C++ to Python layer. Pull Request resolved: https://github.com/pytorch/audio/pull/2423 Reviewed By: carolineechen Differential Revision: D36766152 Pulled By: mthrok fbshipit-source-id: 53f897a608e97b81ebe5df29577374d88ce178f3
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Andrey Talman authored
Summary: This PR adds M1 wheel builds for torchaudio Based on this PR: https://github.com/pytorch/vision/pull/5948 And this Builder [script](https://github.com/pytorch/builder/blob/main/build_m1_domains.sh) Pull Request resolved: https://github.com/pytorch/audio/pull/2421 Reviewed By: mthrok Differential Revision: D36767469 Pulled By: atalman fbshipit-source-id: 9fc3b74b50ee669a230302fd27682702f83f63dc
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- 30 May, 2022 1 commit
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moto authored
Summary: All the unittests jobs are failing due to import error due to protobuf and scipy. This commit pins the versions of them to an older version. ## protobuf https://app.circleci.com/pipelines/github/pytorch/audio/10979/workflows/42005226-ca7e-471c-80f4-db09f4bd2089/jobs/692078 ``` E TypeError: Descriptors cannot not be created directly. E If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. E If you cannot immediately regenerate your protos, some other possible workarounds are: E 1. Downgrade the protobuf package to 3.20.x or lower. E 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower). E E More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates ``` https://github.com/protocolbuffers/protobuf/issues/10051 https://github.com/PyTorchLightning/pytorch-lightning/issues/13159 ## scipy (pypocketfft) 1.8.1 is causing issue. https://app.circleci.com/pipelines/github/pytorch/audio/10980/workflows/470a9361-4cc5-4d7c-9264-28fc8b86f1cb/jobs/692267 ``` ../env/lib/python3.9/site-packages/librosa/core/audio.py:11: in <module> import scipy.signal ../env/lib/python3.9/site-packages/scipy/signal/__init__.py:309: in <module> from . import _sigtools, windows ../env/lib/python3.9/site-packages/scipy/signal/windows/__init__.py:41: in <module> from ._windows import * ../env/lib/python3.9/site-packages/scipy/signal/windows/_windows.py:7: in <module> from scipy import linalg, special, fft as sp_fft ../env/lib/python3.9/site-packages/scipy/fft/__init__.py:91: in <module> from ._helper import next_fast_len ../env/lib/python3.9/site-packages/scipy/fft/_helper.py:3: in <module> from ._pocketfft import helper as _helper ../env/lib/python3.9/site-packages/scipy/fft/_pocketfft/__init__.py:3: in <module> from .basic import * ../env/lib/python3.9/site-packages/scipy/fft/_pocketfft/basic.py:6: in <module> from . import pypocketfft as pfft E ImportError: /home/circleci/project/env/lib/python3.9/site-packages/torch/lib/../../../.././libstdc++.so.6: version `GLIBCXX_3.4.30' not found (required by /home/circleci/project/env/lib/python3.9/site-packages/scipy/fft/_pocketfft/pypocketfft.cpython-39-x86_64-linux-gnu.so) Pull Request resolved: https://github.com/pytorch/audio/pull/2422 Reviewed By: atalman Differential Revision: D36764198 Pulled By: mthrok fbshipit-source-id: 897a79fe9c3165206c2e747147fd0f257fc4f683
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- 29 May, 2022 2 commits
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moto authored
Summary: Add num_frames and bits_per_sample to match with the current `torchaudio.info` capability. Pull Request resolved: https://github.com/pytorch/audio/pull/2418 Reviewed By: carolineechen Differential Revision: D36749077 Pulled By: mthrok fbshipit-source-id: 7b368ee993cf5ed63ff2f53c9e3b1f50fcce7713
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moto authored
Summary: Preparation for upcoming change where load/info function will use fallback if sox_io backend cannot handle the input. Pull Request resolved: https://github.com/pytorch/audio/pull/2416 Reviewed By: carolineechen Differential Revision: D36736969 Pulled By: mthrok fbshipit-source-id: f804cfda3678f13bf0c2f6557a2f82ae42ae3c03
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- 28 May, 2022 1 commit
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moto authored
Summary: Attempt to load ffmpeg extension at the top level import Preparation to use ffmpeg-based I/O as a fallback for sox_io backend. Pull Request resolved: https://github.com/pytorch/audio/pull/2417 Reviewed By: carolineechen Differential Revision: D36736989 Pulled By: mthrok fbshipit-source-id: 0beb6f459313b5ea91597393ccb12571444c54d9
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- 27 May, 2022 1 commit
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moto authored
Summary: * `Streamer` has been renamed to `StreamReader` when it was moved from prototype to beta. This commit applies the same name change to the C++ source code. * Fix miscellaneous lint issues * Make the code compilable on FFmpeg 5 Pull Request resolved: https://github.com/pytorch/audio/pull/2403 Reviewed By: carolineechen Differential Revision: D36613053 Pulled By: mthrok fbshipit-source-id: 69fedd6720d488dadf4dfe7d375ee76d216b215d
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- 26 May, 2022 1 commit
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nateanl authored
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- 24 May, 2022 2 commits
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moto authored
Summary: Follow-up of https://github.com/pytorch/audio/issues/2407, the <script> was not properly closed on pages other than tutorials Pull Request resolved: https://github.com/pytorch/audio/pull/2409 Reviewed By: carolineechen Differential Revision: D36632668 Pulled By: mthrok fbshipit-source-id: 9c0409a8011d77f8689e2dcdc1bd9844d3d31f79
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moto authored
Summary: This commit fixes multiple issues with documentation. https://output.circle-artifacts.com/output/job/23245537-e57b-4b9d-9b81-b3df20996d1f/artifacts/0/docs/tutorials/audio_resampling_tutorial.html 1. Duplicated requirejs The nbsphinx extension introduced in https://github.com/pytorch/audio/pull/2393 pulled a requirejs which caused the initialization script to halt. As a result, the right side bar was left uninitialized. 2. Undefined variable error It turned out that PyTorch's theme expected the downstream projects to define `collapsedSections` variable. Currently console log shows `collapsedSections is not defined`. As a result of this fix, we start to see the + symbol on left side. 3. Fix the behavior of default expand Tweaks the right-side bar initialization behavior so that expand-all only happens once, not at every resize. 4. Overwrite the link to GitHub The `GitHub` tab in main-menu always linked PyTorch core. This commit adds overwrite to torchaudio page Pull Request resolved: https://github.com/pytorch/audio/pull/2407 Reviewed By: carolineechen Differential Revision: D36612904 Pulled By: mthrok fbshipit-source-id: 56aa7623a8925a241cf4790ac77a87424ad9237c
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- 23 May, 2022 3 commits
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Zhaoheng Ni authored
Summary: - The multi-channel functions only support complex-valued tensors for spectrogram and PSD matrices. - The mask can be real-valued or complex-valued, hence there is no explicit assertion for mask. - The shape of input Tensors need to be verified before the computation. For example, the shape of PSD matrix must be `(..., freq, channel, channel)`, the shape of the mask must be `(..., freq, time)`, etc. - The autograd unittest of `apply_beamforming` has wrong dimensions for beamform_weights detected by the assertion check. FIx it in this PR. Pull Request resolved: https://github.com/pytorch/audio/pull/2401 Reviewed By: carolineechen Differential Revision: D36597689 Pulled By: nateanl fbshipit-source-id: 6ad1adebe3726851cc1d865650bdf177a98985f6
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Zhaoheng Ni authored
Summary: The `LibriLightLimited` dataset is created for fine-tuning SSL models, such as Wav2Vec2 and HuBERT. It is a supervised subset of [Libri-Light](https://github.com/facebookresearch/libri-light) dataset. To distinguish the unsupervised subset and the supervised one, it's clearer to put it in a separate dataset class for fine-tuning purpose. It contains "10 min", "1 hour", "10 hour" splits. Pull Request resolved: https://github.com/pytorch/audio/pull/2302 Reviewed By: mthrok Differential Revision: D36388188 Pulled By: nateanl fbshipit-source-id: ba49f1c9996be17db5db41127d8ca96224c94249
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Zhaoheng Ni authored
Summary: Replace https://github.com/pytorch/audio/issues/2129 Pull Request resolved: https://github.com/pytorch/audio/pull/2198 Reviewed By: carolineechen Differential Revision: D36544163 Pulled By: nateanl fbshipit-source-id: 3f19ba5b0f2c2b9e93b0603c3b4491c1dbc40ef8
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- 21 May, 2022 1 commit
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moto authored
Summary: This commit adds file-like object support to Streaming API. ## Features - File-like objects are expected to implement `read(self, n)`. - Additionally `seek(self, offset, whence)` is used if available. - Without `seek` method, some formats cannot be decoded properly. - To work around this, one can use the existing `decoder` option to tell what decoder it should use. - The set of `decoder` and `decoder_option` arguments were added to `add_basic_[audio|video]_stream` method, similar to `add_[audio|video]_stream`. - So as to have the arguments common to both audio and video in front of the rest of the arguments, the order of the arguments are changed. - Also `dtype` and `format` arguments were changed to make them consistent across audio/video methods. ## Code structure The approach is very similar to how file-like object is supported in sox-based I/O. In Streaming API if the input src is string, it is passed to the implementation bound with TorchBind, if the src has `read` attribute, it is passed to the same implementation bound via PyBind 11.  ## Refactoring involved - Extracted to https://github.com/pytorch/audio/issues/2402 - Some implementation in the original TorchBind surface layer is converted to Wrapper class so that they can be re-used from PyBind11 bindings. The wrapper class serves to simplify the binding. - `add_basic_[audio|video]_stream` methods were removed from C++ layer as it was just constructing string and passing it to `add_[audio|video]_stream` method, which is simpler to do in Python. - The original core Streamer implementation kept the use of types in `c10` namespace minimum. All the `c10::optional` and `c10::Dict` were converted to the equivalents of `std` at binding layer. But since they work fine with PyBind11, Streamer core methods deal them directly. ## TODO: - [x] Check if it is possible to stream MP4 (yuv420p) from S3 and directly decode (with/without HW decoding). Pull Request resolved: https://github.com/pytorch/audio/pull/2400 Reviewed By: carolineechen Differential Revision: D36520073 Pulled By: mthrok fbshipit-source-id: a11d981bbe99b1ff0cc356e46264ac8e76614bc6
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- 20 May, 2022 3 commits
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moto authored
Summary: After https://github.com/pytorch/audio/issues/2395, build_doc job is exceeding default no-output-timeout threshould (10m). This commit updates the timeout threshold to 30m. Also it moves the installation of tools to the previous step. Pull Request resolved: https://github.com/pytorch/audio/pull/2399 Reviewed By: carolineechen Differential Revision: D36539022 Pulled By: mthrok fbshipit-source-id: 391764a0fb5bf87cfb2beaab401a90dcb56493e5
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Jeff Hwang authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2392 Refactors LibriSpeech tests to accommodate different dataset classes Reviewed By: xiaohui-zhang Differential Revision: D36387835 fbshipit-source-id: 73b4e7565b4a077b25f036f4bd854ac7f2194b28
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moto authored
Summary: This commit adds tutorial to enable/use NVDEC with Stream API. https://output.circle-artifacts.com/output/job/19e66a4b-1819-4804-8834-d38e6c80c4fd/artifacts/0/docs/hw_acceleration_tutorial.html Because the use of NVDEC requires build / install FFmpeg from source, this tutorial was authored on Google Colab, tailored to its environment. The tutorial here is the result of the notebook execution, with the link to the publicly accessible Google Colab notebook. Pull Request resolved: https://github.com/pytorch/audio/pull/2393 Reviewed By: hwangjeff Differential Revision: D36404408 Pulled By: mthrok fbshipit-source-id: 9c820d3db4d06c5b343ecad0708489125ca06948
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- 19 May, 2022 2 commits
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Eli Uriegas authored
Summary: To resolve nightly / general build issues relating to OpenMP not being found, see https://hud.pytorch.org/pytorch/audio/commit/c6a376cc5679c1940e49fc3e0ba22eaead6c2467 ``` -- Found Torch: /Users/distiller/miniconda3/envs/env3.10/lib/python3.10/site-packages/torch/lib/libtorch.dylib CMake Error at /Users/distiller/miniconda3/envs/env3.10/lib/python3.10/site-packages/cmake/data/CMake.app/Contents/share/cmake-3.22/Modules/FindPackageHandleStandardArgs.cmake:230 (message): Could NOT find OpenMP_C (missing: OpenMP_C_FLAGS OpenMP_C_LIB_NAMES) Call Stack (most recent call first): /Users/distiller/miniconda3/envs/env3.10/lib/python3.10/site-packages/cmake/data/CMake.app/Contents/share/cmake-3.22/Modules/FindPackageHandleStandardArgs.cmake:594 (_FPHSA_FAILURE_MESSAGE) /Users/distiller/miniconda3/envs/env3.10/lib/python3.10/site-packages/cmake/data/CMake.app/Contents/share/cmake-3.22/Modules/FindOpenMP.cmake:544 (find_package_handle_standard_args) CMakeLists.txt:131 (find_package) -- Configuring incomplete, errors occurred! ``` Signed-off-by:
Eli Uriegas <eliuriegas@fb.com> Pull Request resolved: https://github.com/pytorch/audio/pull/2404 Reviewed By: atalman Differential Revision: D36495791 Pulled By: seemethere fbshipit-source-id: 7b6fa2a62fda6fc468cfcbdf8d2163e6b9c327b0
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moto authored
Summary: * Move the helper wrapping code in TorchBind layer to proper wrapper class for so that it will be re-used in PyBind11. * Move `add_basic_[audio|video]_stream` methods from C++ to Python, as they are just string manipulation. This will make PyBind11-based binding simpler as it needs not to deal with dtype. * Move `add_[audio|video]_stream` wrapper signature to Streamer core, so that Streamer directly deals with `c10::optional`.† † Related to this, there is a slight change in how the empty filter expression is stored. Originally, if an empty filter expression was given to `add_[audio|video]_stream` method, the `StreamReaderOutputStream` was showing it as empty string `""`, even though internally it was using `"anull"` or `"null"`. Now `StreamReaderOutputStream` shows the corresponding filter expression that is actually being used. Ref https://github.com/pytorch/audio/issues/2400 Pull Request resolved: https://github.com/pytorch/audio/pull/2402 Reviewed By: nateanl Differential Revision: D36488808 Pulled By: mthrok fbshipit-source-id: 877ca731364d10fc0cb9d97e75d55df9180f2047
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- 18 May, 2022 1 commit
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Zhaoheng Ni authored
Summary: In Wav2Vec2 and HuBERT model training, the convolutional feature extraction layers use `group_norm` for normalization in `Base` model, while they use `layer_norm` in `Large` and `XLarge` models. For `Base` model, the gradients of feature extraction layers will be unstable in pre-training, thus we need to scale down the gradient by multiplying 0.1. In this PR, we add such argument to `HuBERTPretrainModel` to control the gradient of feature extractor layers. We also put the argument in the factory functions (`hubert_pretrain_base`, `hubert_pretrain_large`, and `hubert_pretrain_xlarge`. The reason is in finetuning, the feature extractor's parameters are fixed, we can multiply the gradient with 0.0 to avoid back propagating gradients. Pull Request resolved: https://github.com/pytorch/audio/pull/2335 Reviewed By: xiaohui-zhang, mthrok Differential Revision: D35646928 Pulled By: nateanl fbshipit-source-id: 6a9563e227aac6e3127b634357946d860f26c994
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- 17 May, 2022 1 commit
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moto authored
Summary: This commit updates the `window.sideMenus.handleRightMenu`, so that subsections are expanded on tutorials by default. https://output.circle-artifacts.com/output/job/98508917-87df-4666-9958-c70683b3245d/artifacts/0/docs/tutorials/audio_io_tutorial.html Tutorial subsections are important because they have anchors so allow us to get the link to the specific figures / audio samples. When responding issues/questions and when there is a corresponding code snippet in tutorial, it is often easy to answer with links to the tutorial. However, by default the tutorial page collapses right side bar, and I have to click the small "+" symbols to navigate to the subsection, and the state of expansion does not persist across the page refresh. This has been a pain point since we updated the Sphinx version to 3 in https://github.com/pytorch/audio/pull/1685. Pull Request resolved: https://github.com/pytorch/audio/pull/2397 Reviewed By: xiaohui-zhang Differential Revision: D36429745 Pulled By: mthrok fbshipit-source-id: 97a5ae9270e68f8e88f0bca766d5a2c1839634e3
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