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torchaudio

PyTorch Foundationgithub.com/pytorch/audio

An audio package for PyTorch

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Updated 6 h ago · first seen 11 Sept 2026

lib_01M29ABFFFY73SGA74VS6PHQKJ

Version
2.11.0
T2 · 6 h ago
Released
23 Mar 2026
T2 · 6 h ago
License
BSD License
T2 · 6 h ago

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14 claims · 14 properties

Licenselicense1

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BSD LicensecurrentcurrentPyPI public package metadataT2mediumdeterministic

Repositoryrepository_url1

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https://github.com/pytorch/audiocurrentcurrentPyPI public package metadataT2mediumdeterministic

Authorauthor1

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Soumith Chintala, David Pollack, Sean Naren, Peter Goldsborough, Moto Hira, Caroline Chen, Jeff Hwang, Zhaoheng Ni, Xiaohui ZhangcurrentcurrentPyPI public package metadataT2mediumdeterministic

Descriptiondescription1

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An audio package for PyTorchcurrentcurrentPyPI public package metadataT2mediumdeterministic

Homepagehomepage1

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https://github.com/pytorch/audiocurrentcurrentPyPI public package metadataT2mediumdeterministic

Latest releaselatest_release_at1

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23 Mar 2026currentcurrentPyPI public package metadataT2mediumdeterministic

Latest versionlatest_version1

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2.11.0currentcurrentPyPI public package metadataT2mediumdeterministic

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44currentcurrentPyPI public package metadataT2mediumdeterministic

PyPIpypi1

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torchaudiocurrentcurrentPyPI public package metadataT2mediumdeterministic

Pypi licensepypi_license1

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BSD LicensecurrentcurrentPyPI public package metadataT2mediumdeterministic

Pypi release atpypi_release_at1

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23 Mar 2026currentcurrentPyPI public package metadataT2mediumdeterministic

Pypi urlpypi_url1

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https://pypi.org/project/torchaudio/currentcurrentPyPI public package metadataT2mediumdeterministic

Pypi versionpypi_version1

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2.11.0currentcurrentPyPI public package metadataT2mediumdeterministic

Python classifierspython_classifiers1

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Programming Language :: Python :: 3.10, Programming Language :: Python :: 3.11, Programming Language :: Python :: 3.12, Programming Language :: Python :: 3.13, Programming Language :: Python :: 3.14currentcurrentPyPI public package metadataT2mediumdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →