Hosted on NVIDIA GPU Cloud (NGC) are the following Docker container images for machine learning on Jetson:

• l4t-ml
• l4t-pytorch
• l4t-tensorflow

Included in this repo are the Dockerfiles and scripts used to build the above containers.

To enable access to the CUDA compiler (nvcc) during docker build operations, add "default-runtime": "nvidia" to your /etc/docker/daemon.json configuration file before attempting to build the containers:

{
    "runtimes": {
        "nvidia": {
            "path": "nvidia-container-runtime",
            "runtimeArgs": []
        }
    },

    "default-runtime": "nvidia"
}

You will then want to restart the Docker service or reboot your system before proceeding.

To rebuild the containers from a Jetson device running JetPack 4.4 Developer Preview, clone this repo and run ./scripts/docker_build_all.sh:

$ git clone https://github.com/dusty-nv/jetson-containers
$ cd jetson-containers
$ ./scripts/docker_build_all.sh

Note that the TensorFlow and PyTorch pip wheel installers for aarch64 are automatically downloaded in the Dockerfiles from the Jetson Zoo.

To run a series of automated tests on the packages installed in the containers, run the following from your jetson-containers directory:

$ ./scripts/docker_test.sh