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How to Install PyTorch on Python 3.12.1

Last Updated : 06 Sep, 2024
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Currently, PyTorch does not support Python 3.12, and users attempting to install it on this version will encounter compatibility issues. This article will guide you through the current state of PyTorch installation on Python 3.12, alternatives, and potential workarounds.

Current Status of PyTorch Support for Python 3.12

As of the latest updates, PyTorch does not have pre-built binaries for Python 3.12. Attempts to install PyTorch on Python 3.12 result in errors due to the absence of a suitable version that satisfies the requirements for this Python version. This is a common scenario when new Python versions are released, as libraries like PyTorch need time to update their support.

This is evident from the error messages users encounter when attempting to install PyTorch using pip:

Why Compatibility Takes Time?

The development and release of compatible versions involve extensive testing and adjustments to ensure stability and performance across different systems and configurations. PyTorch, being a complex library with dependencies on various components like CUDA for GPU acceleration, requires meticulous updates to align with new Python versions.

Why PyTorch is Not Yet Available for Python 3.12

PyTorch's development cycle involves extensive testing and validation, which takes time. The library's maintainers need to ensure that all features and dependencies are compatible with new versions of Python. This process includes addressing dependencies and compatibility issues with other libraries, such as Flask, which can also impact the availability of PyTorch.

Alternatives and Workarounds: Downgrading Python

One of the most straightforward solutions is to downgrade your Python version to the latest supported one, which is Python 3.11.x. This allows you to install PyTorch without compatibility issues. Here’s how you can do it:

1. Uninstall Python 3.12:

  • On Windows, go to the Control Panel > Programs > Programs and Features, select Python 3.12, and click Uninstall.
  • On macOS, remove Python 3.12 using Homebrew with the command: brew uninstall [email protected].
  • On Linux, use your package manager to remove Python 3.12.
uninstall
Uninstall Python 3.12

2. Install Python 3.11:

To install Python 3.11 in, you can use the following steps. Google Colab typically comes with Python 3.7 or 3.8, but you can upgrade to Python 3.11 by following these instructions. Note that changing Python versions in Colab is a bit involved and might affect package compatibility.

Python
!sudo apt-get update -y
!sudo apt-get install python3.11 python3.11-distutils -y
!sudo apt-get install python3-pip -y

Output:

Hit:1 http://archive.ubuntu.com/ubuntu jammy InRelease
Get:2 http://archive.ubuntu.com/ubuntu jammy-updates InRelease [128 kB]
Get:3 http://security.ubuntu.com/ubuntu jammy-security InRelease [129 kB]
Get:4 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 InRelease [1,581 B]
Hit:5 http://archive.ubuntu.com/ubuntu jammy-backports InRelease
Get:6 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ InRelease [3,626 B]
.
.
Selecting previously unselected package python3-pip.
Preparing to unpack .../python3-pip_22.0.2+dfsg-1ubuntu0.4_all.deb ...
Unpacking python3-pip (22.0.2+dfsg-1ubuntu0.4) ...
Setting up python3-setuptools (59.6.0-1.2ubuntu0.22.04.1) ...
Setting up python3-wheel (0.37.1-2ubuntu0.22.04.1) ...
Setting up python3-pip (22.0.2+dfsg-1ubuntu0.4) ...
Processing triggers for man-db (2.10.2-1) ...

Best Practices for Managing Python Versions

Given the rapid evolution of Python and the occasional lag in library support, it is crucial to manage different Python versions effectively. Here are some best practices:

  • Use Virtual Environments: Virtual environments like venv or conda help isolate different projects and their dependencies, making it easier to switch between different Python versions.
  • Keep Track of Library Support: Regularly check the official documentation and community forums of the libraries you use to stay updated on their compatibility with different Python versions.
  • Consider Using Package Managers: Package managers like Anaconda can simplify the process of managing multiple Python versions and their dependencies.

Conclusion

Installing PyTorch on Python 3.12.1 currently poses significant challenges due to the lack of pre-built binaries. However, by building PyTorch from source or using older supported versions of Python, users can still leverage the powerful features of PyTorch. As the PyTorch community continues to work on supporting newer versions of Python, it is essential to stay informed through official channels and community forums.


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