Package: python3-torchaudio (2.9.1-1)

[ Source: pytorch-audio  ]

Experimental package

Warning: This package is from the experimental distribution. That means it is likely unstable or buggy, and it may even cause data loss. Please be sure to consult the changelog and other possible documentation before using it.

Data manipulation and transformation for audio signal processing

The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of Pytorch is be seen in torchaudio through having all the computations be through Pytorch operations which makes it easy to use and feel like a natural extension.

Other Packages Related to python3-torchaudio

• dep: libc6 (>= 2.32)

  GNU C Library: Shared libraries
  also a virtual package provided by libc6-udeb

• dep: libgcc-s1 (>= 3.0) [not s390x]

  GCC support library

  dep: libgcc-s1 (>= 4.2) [s390x]

• dep: libgomp1 (>= 4.9)

  GCC OpenMP (GOMP) support library

• dep: libstdc++6 (>= 14)

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• dep: libtorch2.9 (>= 2.9.1+dfsg)

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  or libtorch-cuda-2.9 (>= 2.9.1+dfsg)

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  or libtorch-rocm-2.9 (>= 2.9.1+dfsg)

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  or python3-torch-cuda

  Tensors and Dynamic neural networks in Python (Python Interface)

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Architecture	Package Size	Installed Size	Files
amd64	345.8 kB	1,692.0 kB	[list of files]
arm64	317.6 kB	1,677.0 kB	[list of files]
ppc64el	344.6 kB	1,805.0 kB	[list of files]
s390x	338.2 kB	1,685.0 kB	[list of files]