Build a Linux 4 Tegra with CUDA Ubuntu 22.04 docker image for the nVidia Jetson Nano using its final JetPak 4.6.3

Dockerfile

# Make an Ubuntu 22.04 Docker image supporting CUDA and Linux 4 Tegra stuff on
# the nVidia Jetson Nano.  I ran this from the final nano Linux 4 Tegra JetPak
# image aka jetson-nano-jp461-sd-card-image.zip which I updated to 4.6.3
# using apt.  -- @gpshead
#
# Is there any real point to doing this?  I have no idea. :P
# If you don't care about toying with the GPU stuff, just go install Armbian.
#
# This is based off of the instructions on
# https://github.com/NVIDIA/nvidia-docker/wiki/NVIDIA-Container-Runtime-on-Jetson
# and the final Jetpak 32.x container that represents the final Jetson Nano
# platform from https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-base
# before nvidia went ass-hole and abandoned three generations of hardware that
# they still ship.

FROM nvcr.io/nvidia/l4t-base:r32.7.1

RUN apt-get update && apt-get upgrade -y
RUN apt-get install ubuntu-release-upgrader-core -y --no-install-recommends
# 18.04 -> 20.04
RUN do-release-upgrade -f DistUpgradeViewNonInteractive

RUN apt-get update && apt-get upgrade -y
RUN apt-get clean
RUN apt-get install -y --no-install-recommends vim
# 20.04 -> 22.04 and IGNORE the error (which should be from usrmerge.postinstall)
RUN do-release-upgrade -f DistUpgradeViewNonInteractive ; exit 0
# Patch the failed convert-usrmerge to work around https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=1008202
RUN sed -i -e 's/no autodie;/rm(\"-rf\", \"$dir\");/g' -e 's/not rename/0 \&\& not rename/g' /usr/lib/usrmerge/convert-usrmerge
# Continue the last bit do-release-upgrade failed to do? (is this really enough?)
RUN dpkg --configure -a
RUN apt-get remove python2 -y
RUN apt-get autoremove -y
RUN apt-get clean

# All done here, the rest just proves that this 22.04 container supports CUDA.
# You MUST pass the `--runtime nvidia` flag to `docker run` for CUDA to work.

RUN apt-get install -y --no-install-recommends make g++
COPY ./samples /tmp/samples

WORKDIR /tmp/samples/1_Utilities/deviceQuery
RUN make clean && make

CMD ["./deviceQuery"]

Starting to run through this - if anyone else is following this, on installed clean image of jetpack 4.6.3, after running sudo apt update && sudo apt upgrade -y, the command sudo apt install nvidia-jetpack is likely to fail. The fix for that is:

sudo apt dist-upgrade
sudo apt update
sudo apt-get install nvidia-container
sudo apt-get install nvidia-jetpack

Hey guys!

Thanks for the suggestions. based on this, i upgraded the kernal of nvidia's r32.7.1 docker container and created a new base container with ubuntu focal 20.04. Tried to push it up to ubuntu 22.04 jammy but didnt proceed as it drops support for gcc8 and g++8 which is needed by cuda10.2 in jetson nano.

docker files and terminal commands are here https://github.com/KalanaRatnayake/jetson-docker

At the moment i provide a base container (822 MB) and a test container that is built on top of it (1.11GB) so that sizes stay low.

Will keep adding new images that extend the use cases of this