container-images VS toolbox

FROM tensorflow/tensorflow:1.15.5-gpu-py3 # Handle Nvidia public key update and update repositories for Ubuntu 18.x. #https://github.com/sangyun884/HR-VITON/issues/45 # reference: https://jdhao.github.io/2022/05/05/nvidia-apt-repo-public-key-error-fix/ RUN rm /etc/apt/sources.list.d/cuda.list RUN rm /etc/apt/sources.list.d/nvidia-ml.list RUN apt-key del 7fa2af80 # Additional reference: https://gitlab.com/nvidia/container-images/cuda/-/issues/158 RUN export this_distro="$(cat /etc/os-release | grep '^ID=' | awk -F'=' '{print $2}')" \ && export this_version="$(cat /etc/os-release | grep '^VERSION_ID=' | awk -F'=' '{print $2}' | sed 's/[^0-9]*//g')" \ && apt-key adv --fetch-keys "https://developer.download.nvidia.com/compute/cuda/repos/${this_distro}${this_version}/x86_64/3bf863cc.pub" \ && apt-key adv --fetch-keys "https://developer.download.nvidia.com/compute/machine-learning/repos/${this_distro}${this_version}/x86_64/7fa2af80.pub" # get the latest version of OpenCV RUN apt-get update && \ DEBIAN_FRONTEND=noninteractive \ apt-get install -y -qq \ wget git libopencv-dev RUN python -m pip install --upgrade pip && \ pip install matplotlib opencv-python==4.5.4.60 Pillow scipy \ azure-eventhub azure-eventhub-checkpointstoreblob-aio ipykernel WORKDIR /

As far as I can see, the way Google Chrome developers chose to support hardware acceleration under Linux is through Vulkan (here and here) According to Nvidia, there's no official support for Vulkan inside Docker. Although it seems that FAQ hasn't been updated because I was able to find a Docker container with Vulkan support here.

Looking forward to the CUDA containers getting released!

# Based on https://gitlab.com/nvidia/container-images/l4t-base/-/blob/master/Dockerfile.l4t # https://github.com/dusty-nv/jetson-containers/blob/master/Dockerfile.ros.foxy # https://github.com/codustry/jetson-containers/blob/master/Dockerfile.ros.foxy ARG L4T_MINOR_VERSION=5.0 FROM codustry/ros:foxy-ros-base-l4t-r32.${L4T_MINOR_VERSION} # # ZED Jetson # https://github.com/stereolabs/zed-docker/blob/master/3.X/jetpack_4.X/devel/Dockerfile # ARG ZED_SDK_MAJOR=3 ARG ZED_SDK_MINOR=5 ARG JETPACK_MAJOR=4 ARG JETPACK_MINOR=5 #This environment variable is needed to use the streaming features on Jetson inside a container ENV LOGNAME root ENV DEBIAN_FRONTEND noninteractive RUN apt-get update -y && apt-get install --no-install-recommends lsb-release wget less udev sudo apt-transport-https build-essential cmake openssh-server libv4l-0 libv4l-dev v4l-utils binutils xz-utils bzip2 lbzip2 curl ca-certificates libegl1 python3 -y && \ echo "# R32 (release), REVISION: 5.0" > /etc/nv_tegra_release ; \ wget -q --no-check-certificate -O ZED_SDK_Linux_JP.run https://download.stereolabs.com/zedsdk/${ZED_SDK_MAJOR}.${ZED_SDK_MINOR}/jp${JETPACK_MAJOR}${JETPACK_MINOR}/jetsons && \ chmod +x ZED_SDK_Linux_JP.run ; ./ZED_SDK_Linux_JP.run silent skip_tools && \ rm -rf /usr/local/zed/resources/* \ rm -rf ZED_SDK_Linux_JP.run && \ rm -rf /var/lib/apt/lists/* #This symbolic link is needed to use the streaming features on Jetson inside a container RUN ln -sf /usr/lib/aarch64-linux-gnu/tegra/libv4l2.so.0 /usr/lib/aarch64-linux-gnu/libv4l2.so # # Configure Enviroment for ROS RUN echo 'source /opt/ros/foxy/install/setup.bash' >> ~/.bashrc # RUN echo "source /opt/ros/eloquent/setup.bash" >> ~/.bashrc RUN echo 'source /usr/share/colcon_cd/function/colcon_cd.sh' >> ~/.bashrc # RUN echo "export _colcon_cd_root=~/ros2_install" >> ~/.bashrc # echo $LD_LIBRARY_PATH RUN echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-10.2/targets/aarch64-linux/lib/stubs:/opt/ros/foxy/install/lib' >> ~/.bashrc WORKDIR /root/Downloads RUN wget https://developer.nvidia.com/embedded/L4T/r32_Release_v5.0/T186/Tegra186_Linux_R32.5.0_aarch64.tbz2 RUN tar xf Tegra186_Linux_R32.5.0_aarch64.tbz2 RUN cd Linux_for_Tegra && \ sed -i 's/config.tbz2\"/config.tbz2\" --exclude=etc\/hosts --exclude=etc\/hostname/g' apply_binaries.sh && \ sed -i 's/install --owner=root --group=root \"${QEMU_BIN}\" \"${L4T_ROOTFS_DIR}\/usr\/bin\/\"/#install --owner=root --group=root \"${QEMU_BIN}\" \"${L4T_ROOTFS_DIR}\/usr\/bin\/\"/g' nv_tegra/nv-apply-debs.sh && \ sed -i 's/LC_ALL=C chroot . mount -t proc none \/proc/ /g' nv_tegra/nv-apply-debs.sh && \ sed -i 's/umount ${L4T_ROOTFS_DIR}\/proc/ /g' nv_tegra/nv-apply-debs.sh && \ sed -i 's/chroot . \// /g' nv_tegra/nv-apply-debs.sh && \ ./apply_binaries.sh -r / --target-overlay RUN rm -rf Tegra210_Linux_R32.4.4_aarch64.tbz2 && \ rm -rf Linux_for_Tegra && \ echo "/usr/lib/aarch64-linux-gnu/tegra" > /etc/ld.so.conf.d/nvidia-tegra.conf && ldconfig WORKDIR /usr/local/zed ENV CUDA_HOME=/usr/local/cuda WORKDIR /root/ros2_ws/src/ RUN source /opt/ros/foxy/install/setup.bash && cd ../ && colcon build --symlink-install RUN git clone https://github.com/stereolabs/zed-ros2-wrapper.git RUN git clone https://github.com/ros/diagnostics.git && cd diagnostics && git checkout foxy WORKDIR /root/ros2_ws RUN source /opt/ros/foxy/install/setup.bash && source $(pwd)/install/local_setup.bash && rosdep update && \ rosdep install --from-paths src --ignore-src -r --rosdistro ${ROS_DISTRO} -y && \ colcon build --symlink-install --cmake-args " -DCMAKE_BUILD_TYPE=Release" " -DCMAKE_LIBRARY_PATH=/usr/local/cuda/lib64/stubs" " -DCUDA_CUDART_LIBRARY=/usr/local/cuda/lib64/stubs" " -DCMAKE_CXX_FLAGS='-Wl,--allow-shlib-undefined'" && \ echo source $(pwd)/install/local_setup.bash >> ~/.bashrc && \ source ~/.bashrc

That leaves Flatcar and Clear Linux - both of which happen to at least have documentation for installing/running Nvidia drivers and CUDA. Flatcar has this repository from Nvidia, and I've also found this project called forklift which will supposedly handle auto-updating the kernel modules for you. The Clear Linux docs also seem to include a method to auto-rebuild the modules with kernel upgrades, though it does say that the driver version needs to be updated manually, which honestly almost sounds preferable considering how finicky Nvidia drivers can be on Linux. Clear Linux also has several other tutorials/guides that appear to try and market it for things like machine learning, which leads me to believe that Nvidia gpus would hopefully work decently on it.

To add CUDA I plan on adding the stuff from this Docker script.

You can use the cuda dockerfile as reference: https://gitlab.com/nvidia/container-images/cuda/-/blob/master/Dockerfile

However, getting Nvidia to work was much more complicated. Now, I am not a container expert, so a lot of it was because of my unfamiliarity with the technology. At first, I had to get nvidia-container-toolkit using CentOS package. The test containers given in the instructions here worked fine. However, I soon understood that nvidia-container-toolkit requires basing the image on nvidia official containers or going through this and figure out how to create a custom container. Most documentation online seemed to be about nvidia-docker or just covered the install portion of nvidia-container-toolkit. There was almost nothing available on how to create a custom image. After some digging around and copying and pasting (I still don't understand some of it), I was able to create a container with nvidia-smi, and other cuda commands working.

https://gitlab.com/nvidia/container-images/cuda/-/issues/109#note_503061879

The team has both made a ton of effort switching off their proprietary Skia based rendering tech and adopting standard Wayland, and has put forward huge effort to making running incredibly well integrated real Linux containers just work.

The headline is true. ChromeOS is Linux with Google’s desktop environment. But it obfuscates the details. It's a damned by omission statement. It has some really good sauce to help you not notice often, but it's not at all a Linux desktop environment one can regularly use. You can do a lot of Linux desktop-y things but only through well crafted special unique wrapped processes that mostly but not fully help mock & emulate a regular Linux desktop. Even though it now runs Wayland, the apps you want to run will have atypical intermediates up the wazoo.

And no one else uses any of this tech. ChromiumOs has so much interesting container tech, does such an interesting job making containers think they have a regular Linux / FreeDesktop environment. It's far far far far deeper virtualization than for example https://github.com/containers/toolbox . But you know what? Google has made zero effort to get these pieces adopted elsewhere. It's open source but not intended for use outside Chromium/ChromeOS. I respect & think ChromeOS is a quite viable Linux, and it's so much closer to the metal & more interesting, amazing tech, but my gods Microsoft has gone 300x further to establish wsl2 as a sustainable community effort folks could use & target, in a way that ChromiumOS has done nothing about.

It's sad how Google has transformed from a company that appreciated & worked with ecosystems, that drove things collectively forward, into an individual player that does their own things & delivers from on high. ChromiumOS is such an incredible effort, but it's so internernally drive & focused, and it's hard to believe in such a wildcat effort, even though it's so so good. It keeps coming into better alignment with Linux Desktop actual, but via shims and emulations that no one else cares about or which seems marketed elsewhere. And that inward focus makes the whole effort both so exceptional & promising, but suspect. Such a different nearby but alternative & separately governed universe. ChromiumOS/ChromeOS do excellent at faking being a Linux desktop, and wonderfully have increasingly drawn more strength from that universe, but are still wholly their own very distinct very separate very controller other space. In many ways that's great, secure, good, and miraculously transparently done. But it's still hard to really trust, being such a weird alien impostor, faking so much for end user apps, and there's tension in believing ChromeOS will keep straddling the rift in pro-user manifestations forever.

I'm really, really happy with my current setup of Fedora immutable + toolbox [0]. This tool lets you create containers that are fully integrated with the system, so you have acces to the entire Fedora repos, can run graphical apps, etc. while still having everything inside a container in your home directory. That means no Flatpak required. Highly recommended.

[0] https://containertoolbx.org

Seems like toolbox is also in this space; https://github.com/containers/toolbox

With Silverblue the core repos are very similar to what you'd have on regular Fedora. With more of a philosophical shift about where you're supposed to install things from. The idea being that the base OS is immutable and you keep it fairly minimal - even though you are technically free to install any of Fedora packages to it. And then you install user applications through Flatpak and toolbx. Where these more user space focussed applications are installed to your home directory and are sandboxed away from actual access to your OS. With iOS/Android style application permissions like "Give app permission to access camera" and "Give app permission to modify files in home directory". Allowing you even further customise the sandboxing of applications. Do you really want that app to have access to your microphone?

I'd probably try running it on the host system first. If you want to use your nvidia gpu inside toolbox, you would indeed need to install the drivers in the container: https://github.com/containers/toolbox/issues/116

Use toolbox on CentOS or Ubuntu if you want a Fedora environment with more up to date tools: https://containertoolbx.org/