Install PyTorch on Jetson Nano.
Last updated: July 17, 2022
This page will guide you through the installation of PyTorch, TorchVision, LibTorch and Caffe2 on a Jetson Nano.
PyTorch is a software library specially developed for deep learning. It consumes an lot of resources of your Jetson Nano. So, don't expect miracles. It can run your models, but it can't train new models. The so-called transfer learning can cause problems due to the limited amount of available RAM.
We discuss two installations, one with a Python 3 wheel. The other method is the build from scratch. Unfortunately, there is no official pip3 wheel available for the Jetson Nano. However, we created these wheels and put them on GitHub for your convenience.
PyTorch 1.12, 1.11.
PyTorch version 1.11 and above requires Python 3.7, found in JetPack 5.0.
Since JetPack 4.6 has Python 3.6, you cannot install PyTorch 1.11.0 on a Jetson Nano.
It looks like Nvidia has no plans to release the new JetPack 5.0 for the Jetson Nano for now. It's only available for the Xavier series.
However, you can use the current version of Jetson Nano with Ubuntu 20.04. We supply the wheels for this version at GitHub.
PyTorch 1.10 has the usual improvements and bug fixes. Please note, some operations have different behavior compared to version 1.9. Take a look at the changelog.
Some warnings about version 1.9.0. As seen here, quite a few changes are made to the software since the last version. Not all operations and declarations are supported anymore. It can cause backward compatibility issues when your 1.8 networks are running on this new version.
Installation by wheel.
PyTorch is build by Ninja. It takes more then 5 hours to complete the whole build. We have posted the wheels on our GitHub page. Feel free to use these. With all the tedious work already done, it takes now only a couple of minutes to install PyTorch on your Nano. For the diehards, the complete procedure is covered later in this manual.
The whole shortcut procedure is found below. The wheel was too large to store at GitHub, so Google drive is used. Please make sure you have latest pip3 and python3 version installed, otherwise, pip may come with the message ".whl is not a supported wheel on this platform".
See out GitHub page for all the wheels.