How to reproduce exactly L4T 32.5.1 / Jetpack 4.5.1 / Ubuntu 18.04 inside a docker container

Hello to everyone.

I’ve got an idea that I want to discuss with you. I would like to upgrade ubuntu 18.04 that I have on the jetson nano to version 21.04 and at the same time I want to install the L4T 32.5.1 and the jetpack 4.5.1 with ubuntu 18.04 inside a docker container. In other words,inside the docker container there should be a system like this :

NVIDIA Jetson Nano (Developer Kit Version)
L4T 32.5.1 [ JetPack 4.5.1 ]
Ubuntu 18.04.5 LTS
Kernel Version: 4.9.201+
Xlib: extension “NV-GLX” missing on display “localhost:10.0”.
Xlib: extension “NV-GLX” missing on display “localhost:10.0”.
Xlib: extension “NV-GLX” missing on display “localhost:10.0”.
CUDA 11.0.207
CUDA Architecture: 5.3
OpenCV version: 4.1.1
OpenCV Cuda: NO
CUDNN: 8.0.0.180
TensorRT: 7.1.3.0
Vision Works: 1.6.0.501
VPI: ii libnvvpi1 1.0.15 arm64 NVIDIA Vision Programming Interface library
Vulcan: 1.2.70

it’s the same system that everyday I use as main system on my jetson nano. As primary OS I want to have the most updated ubuntu version,that at the moment is the 21.04. What do u think about this idea ? Do u have some good suggestion and tutorial that I can learn ?

I made an experiment. I created a dockerfile like this one :

FROM ubuntu:18.04

LABEL maintainer "NVIDIA CORPORATION <cudatools@nvidia.com>"

RUN apt-get update && apt-get install -y --no-install-recommends \
    gnupg2 curl ca-certificates && \
    curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/sbsa/7fa2af80.pub | apt-key add - && \
    echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/sbsa /" > /etc/apt/sources.list.d/cuda.list && \
    apt-get purge --autoremove -y curl \
    && rm -rf /var/lib/apt/lists/*

ENV CUDA_VERSION 11.3.1

# For libraries in the cuda-compat-* package: https://docs.nvidia.com/cuda/eula/index.html#attachment-a
RUN apt-get update && apt-get install -y --no-install-recommends \
    cuda-cudart-11-3=11.3.109-1 \
    && ln -s cuda-11.3 /usr/local/cuda && \
    rm -rf /var/lib/apt/lists/*

# Required for nvidia-docker v1
RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf \
    && echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf

ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64

#COPY NGC-DL-CONTAINER-LICENSE /

# nvidia-container-runtime
ENV NVIDIA_VISIBLE_DEVICES all
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
ENV NVIDIA_REQUIRE_CUDA "cuda>=11.2"

but it didn’t work. It gave this error :

root@zi-desktop:~/Desktop/zi/Work/I9/Virt/dockers/arm64/nvidia-docker# ./run.sh

docker: Error response from daemon: OCI runtime create failed: container_linux.go:380: starting container process caused: process_linux.go:545: container init caused: Running hook #0:: error running hook: exit status 1, stdout: , stderr: exec command: [/usr/bin/nvidia-container-cli --load-kmods configure --ldconfig=@/sbin/ldconfig.real --device=all --compute --utility --require=cuda>=11.2 --pid=19186 /var/lib/docker/overlay2/bbd6118701a9488d09f9a48b431bd2458772721f04ac7ebcc199cf30775429d1/merged]
nvidia-container-cli: requirement error: unsatisfied condition: cuda >= 11.2: unknown.

what’s the reason of this error ? because on the main OS I’m using > CUDA 11.0.207 and I can’t use CUDA 11.3 inside docker ?

Hi,

Do you want to build a Jetson docker on the host?
If yes, please follow the guidelines below:

You will need to install the host CUDA library from JetPack for compatibility.

Thanks.

@AastaLLL would jetson GPU cuda samples run from such containers on x86? is GPU virtualization supported?

root@Z390-AORUS-PRO:/home/ziomario/Scrivania/Virt/dockers/docker-build# docker build -t docker://zi/devicequer
y .

invalid argument “docker://zi/devicequery” for “-t, --tag” flag: invalid reference format
See ‘docker build --help’.

root@Z390-AORUS-PRO:/home/ziomario/Scrivania/Virt/dockers/docker-build# docker build .

Sending build context to Docker daemon 2.048kB
Step 1/6 : FROM nvcr.io/nvidia/l4t-base:r32.3.1
r32.3.1: Pulling from nvidia/l4t-base
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f0b6e413c48c: Pull complete
Digest: sha256:e8987d52ddb9496948e02656fc62d46561abce25bfe83203f4bc24c67e094578
Status: Downloaded newer image for nvcr.io/nvidia/l4t-base:r32.3.1
—> aaaa63e7b12d
Step 2/6 : RUN apt-get update && apt-get install -y --no-install-recommends make g++

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binutils binutils-aarch64-linux-gnu binutils-common cpp cpp-7 g+±7 gcc
gcc-7 gcc-7-base gcc-8-base libasan4 libatomic1 libbinutils libc-dev-bin
libc6 libc6-dev libcc1-0 libgcc-7-dev libgcc1 libgomp1 libitm1 liblsan0
libstdc+±7-dev libstdc++6 libtsan0 libubsan0 linux-libc-dev

Suggested packages:
binutils-doc cpp-doc gcc-7-locales gcc-7-doc libstdc++6-7-dbg gcc-multilib
manpages-dev autoconf automake libtool flex bison gdb gcc-doc libgcc1-dbg
libgomp1-dbg libitm1-dbg libatomic1-dbg libasan4-dbg liblsan0-dbg
libtsan0-dbg libubsan0-dbg libcilkrts5-dbg libmpx2-dbg libquadmath0-dbg
glibc-doc libstdc+±7-doc make-doc
Recommended packages:
manpages manpages-dev

The following NEW packages will be installed:
binutils binutils-aarch64-linux-gnu binutils-common g++ g+±7 gcc gcc-7
libasan4 libatomic1 libbinutils libc-dev-bin libc6-dev libcc1-0 libgcc-7-dev
libitm1 liblsan0 libstdc+±7-dev libtsan0 libubsan0 linux-libc-dev make
The following packages will be upgraded:
cpp cpp-7 gcc-7-base gcc-8-base libc6 libgcc1 libgomp1 libstdc++6
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—> 7e59a3532a1c
Step 3/6 : COPY ./samples /tmp/samples

COPY failed: file not found in build context or excluded by .dockerignore: stat samples: file does not exist

root@Z390-AORUS-PRO:/home/ziomario/Scrivania/Virt/dockers/docker-build# docker images

REPOSITORY TAG IMAGE ID CREATED SIZE
none none 7e59a3532a1c 19 seconds ago 1.42GB

Hi,

CUDA-based sample should work.
But some hardware related example, like VIC, is not supported virtually within the x86 container.

Thanks.

Hi,

Step 3/6 : COPY ./samples /tmp/samples

COPY failed: file not found in build context or excluded by .dockerignore: stat samples: file does not exist

The error indicates the ./samples folder doesn’t exist.
Please remember to copy it from the CUDA folder into the docker workspace first.

$ cp -r /usr/local/cuda/samples /tmp

Thanks.

but it won’t be x86, container, it would be arm aarch64 container, right?

On PC,it uses qemu x86 to emulate aarch64,so it’s 50 % and 50% :)

Hi, marietto2008

Do you fix the issue after copying the example into the workspace?
Thanks.

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