Machine Learning Containers for Jetson and JetPack
Modular container build system that provides various AI/ML packages for NVIDIA Jetson
See the packages
directory for the full list, including pre-built container images and CI/CD status for JetPack/L4T.
Using the included tools, you can easily combine packages together for building your own containers. Want to run ROS2 with PyTorch and Transformers? No problem - just do the system setup, and build it on your Jetson like this:
$ ./build.sh --name=my_container ros:humble-desktop pytorch transformers
There are shortcuts for running containers too - this will pull or build a l4t-pytorch
image that's compatible:
$ ./run.sh $(./autotag l4t-pytorch)
run.sh
forwards arguments todocker run
with some defaults added (like--runtime nvidia
, mounts a/data
cache, and detects devices)
autotag
finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.
If you look at any package's readme (like l4t-pytorch
), it will have detailed instructions for running it's container.
Documentation
Looking for the old jetson-containers? See the legacy
branch