dustynv/l4t-pytorch repository overview

To start the container, you can use jetson-containers run⁠ and autotag⁠, or manually put together a docker run⁠ command:

# automatically pull or build a compatible container image
jetson-containers run $(autotag l4t-pytorch)

# or explicitly specify one of the container images above
jetson-containers run dustynv/l4t-pytorch:r36.2.0

# or if using 'docker run' (specify image and mounts/ect)
sudo docker run --runtime nvidia -it --rm --network=host dustynv/l4t-pytorch:r36.2.0

To mount your own directories into the container, use the -v⁠ or --volume⁠ flags:

jetson-containers run -v /path/on/host:/path/in/container $(autotag l4t-pytorch)

To launch the container running a command, as opposed to an interactive shell:

jetson-containers run $(autotag l4t-pytorch) my_app --abc xyz

You can pass any options to it that you would to docker run⁠, and it'll print out the full command that it constructs before executing it.

If you use ⁠autotag⁠ as shown above, it'll ask to build the container for you if needed. To manually build it, first do the system setup⁠, then run:

jetson-containers build l4t-pytorch

The dependencies from above will be built into the container, and it'll be tested during. Run it with --help⁠ for build options.