How to Install and Uninstall python3-torch Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 14,2024

1. Install "python3-torch" package

Please follow the guidance below to install python3-torch on Ubuntu 21.10 (Impish Indri)

$ sudo apt update $ sudo apt install python3-torch

2. Uninstall "python3-torch" package

In this section, we are going to explain the necessary steps to uninstall python3-torch on Ubuntu 21.10 (Impish Indri):

$ sudo apt remove python3-torch $ sudo apt autoclean && sudo apt autoremove

3. Information about the python3-torch package on Ubuntu 21.10 (Impish Indri)

Package: python3-torch
Architecture: amd64
Version: 1.7.1-7
Priority: optional
Section: universe/python
Source: pytorch
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Deep Learning Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 31834
Provides: python3.9-torch
Depends: libtorch1.7 (= 1.7.1-7), python3 (<< 3.10), python3 (>= 3.9~), python3-future, python3-numpy (>= 1:1.16.0~rc1), python3-numpy-abi9, python3-pkg-resources, python3-requests, python3-six, python3-typing-extensions, python3-yaml, python3.9:any, python3:any, libc6 (>= 2.33), libdnnl2 (>= 2.0), libgcc-s1 (>= 3.0), libgloo0 (>= 0.0~git20200918.3dc0328), libgoogle-glog0v5 (>= 0.4.0), libonnx1 (>= 1.7.0+dfsg), libprotobuf23 (>= 3.12.4), libstdc++6 (>= 9), libunwind8
Recommends: libtorch-dev (= 1.7.1-7), build-essential, ninja-build, pybind11-dev
Suggests: python3-hypothesis, python3-pytest
Filename: pool/universe/p/pytorch/python3-torch_1.7.1-7_amd64.deb
Size: 6177668
MD5sum: 52606a6aa131c842ddfffefc5e771473
SHA1: 60312121597b89ec066cfc7430835c63212e0062
SHA256: eaf09c57597d9737170d087e8111643095494579465c3c6dd2e823bf1b3033e3
SHA512: 57a3e8d5681fca9b8b6e92ece71e5ad6881d63f826b70f8f596390a2cbe481d7ab02af3dc880bad9db1e52e25f6a47cc9a73e41a0b27afc03090cac8c4e14515
Homepage: https://pytorch.org/
Description-en: Tensors and Dynamic neural networks in Python with strong GPU acceleration
PyTorch is a Python package that provides two high-level features:
.
(1) Tensor computation (like NumPy) with strong GPU acceleration
(2) Deep neural networks built on a tape-based autograd system
.
You can reuse your favorite Python packages such as NumPy, SciPy and Cython
to extend PyTorch when needed.
.
This is the CPU-only version of PyTorch and Caffe2 (Python interface).
Description-md5: ff49415f4d020ed13f16fd627f3f22cf