From Fedora Project Wiki

PyTorch Release


This change will bring the first iteration of PyTorch to Fedora.


This project is owned by the

Current status

Detailed Description

The goal of packaging PyTorch for Fedora is to make this open-source machine learning framework easily accessible and seamlessly integrable within the Fedora Linux ecosystem. By providing PyTorch as a packaged software in the Fedora repositories, users gain simplified installation and maintenance processes. This enhances the accessibility of PyTorch for Fedora users, fostering a conducive environment for developers, researchers, and enthusiasts to leverage the capabilities of this powerful machine learning framework. Additionally, packaging PyTorch for Fedora contributes to the broader open-source community by promoting collaborative development and innovation in the field of machine learning on the Fedora platform.


The PyTorch SIG meets bi weekly, contributing to the meeting is the best way to engage with what is happening. TBD: Add how to join. The feedback so far has been positive with some high level feature requests. GPU Acceleration More packages that use PyTorch Improving base PyTorch

Benefit to Fedora

This change will introduce PyTorch, a high demand machine learning framework, to Fedora. PyTorch is widely used for tasks such as image and speech recognition, natural language processing, and other artificial intelligence applications, providing a user-friendly interface for building and experimenting with complex machine learning models. This is for CPU (x86_64 and aarch64) only and is the first release for Fedora. The current development effort is focused on AMD GPU acceleration.


  • Proposal owners:

This change does not affect other parts of the distribution and is an isolated change.

  • Other developers:

To install use > dnf install python-torch

  • Release engineering: N/A (not needed for this Change)
  • Policies and guidelines: N/A (not needed for this Change)
  • Trademark approval: N/A (not needed for this Change)
  • Alignment with Community Initiatives: Yes

Upgrade/compatibility impact

This is the first time this package has been available.

How To Test

The PyTorch code base is very large, start with the public examples described here

User Experience

How the user installs PyTorch changes from > pip install torch To > dnf install python-torch

The pip install requires local building which may fail and will not be consistent from machine to machine. Dnf will always succeed and be consistent.


PyTorch is available for Rawhide.

Contingency Plan

  • Contingency mechanism: PyTorch is available for Rawhide.
  • Contingency deadline: N/A (not a System Wide Change)
  • Blocks release? N/A (not a System Wide Change)


There is a wealth of online and print documentation available. A good place to start is the main project page

Release Notes

PyTorch 2.1.2 and some supporting packages are available in F40