
Install PyTorch on Jetson Nano.
Introduction.
This page will guide you through the installation of PyTorch 1.7.0, 1.7.1 or 1.8.0, TorchVision 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.
PyTorch runs on Python. A C++ API is available, but we have not tested it.
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.
The 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.
Pytorch 1.8 for Python 3.
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".
JetPack 4 comes with Python 3.6.9. Undoubtedly, the Python version will upgrade over time and you will need a different wheel. See out GitHub page for all the wheels.
