[ 源代码： pytorch-audio ]
软件包：python3-torchaudio（2.9.1-1）
试制（Experimental）软件包
警告：这个软件包来自于 experimental 发行版。这表示它很有可能表现出不稳定或者出现 bug ，甚至是导致资料损失。请务必在使用之前查阅 changelog 以及其他潜在的文档。
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.
其他与 python3-torchaudio 有关的软件包
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- dep: libc6 (>= 2.32)
- GNU C 语言运行库：共享库
同时作为一个虚包由这些包填实： libc6-udeb
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- dep: libgcc-s1 (>= 3.0) [除 s390x]
- GCC 支持库
- dep: libgcc-s1 (>= 4.2) [s390x]
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- dep: libgomp1 (>= 4.9)
- GCC OpenMP（GOMP）支持库
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- dep: libstdc++6 (>= 14)
- GNU 标准 C++ 库，第3版
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- dep: libtorch2.9 (>= 2.9.1+dfsg)
- Tensors and Dynamic neural networks in Python (Shared Objects)
- 或者 libtorch-cuda-2.9 (>= 2.9.1+dfsg)
- 软件包暂时不可用
- 或者 libtorch-rocm-2.9 (>= 2.9.1+dfsg)
- 软件包暂时不可用
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- dep: python3
- interactive high-level object-oriented language (default python3 version)
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- dep: python3-torch
- Tensors and Dynamic neural networks in Python (Python Interface)
- 或者 python3-torch-cuda
- Tensors and Dynamic neural networks in Python (Python Interface)
- 或者 python3-torch-rocm
- 软件包暂时不可用