container-images
nvidia-docker
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container-images | nvidia-docker | |
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9 | 53 | |
- | 16,998 | |
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- | 0.0 | |
- | 4 months ago | |
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- | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
container-images
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Accelerate Machine Learning Local Development and Test Workflows with Nvidia Docker
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}${this_version}/x86_64/7fa2af80.pub" # get the latest version of OpenCV RUN apt-get update && \ DEBIAN_FRONTEND=noninteractive \ apt-get install -y -qq \ wget git libopencv-dev RUN python -m pip install --upgrade pip && \ pip install matplotlib opencv-python==4.5.4.60 Pillow scipy \ azure-eventhub azure-eventhub-checkpointstoreblob-aio ipykernel WORKDIR /
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How to build ZED 2i Camera x ROS2 Foxy x Nvidia Jetson x Ubuntu 18.04 via Docker
# Based on https://gitlab.com/nvidia/container-images/l4t-base/-/blob/master/Dockerfile.l4t # https://github.com/dusty-nv/jetson-containers/blob/master/Dockerfile.ros.foxy # https://github.com/codustry/jetson-containers/blob/master/Dockerfile.ros.foxy ARG L4T_MINOR_VERSION=5.0 FROM codustry/ros:foxy-ros-base-l4t-r32.${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
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Running Nvidia drivers in Clear Linux or Flatcar?
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.
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Is it possible to install Nvidia drivers?
To add CUDA I plan on adding the stuff from this Docker script.
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Can you add CUDA to a docker container?
You can use the cuda dockerfile as reference: https://gitlab.com/nvidia/container-images/cuda/-/blob/master/Dockerfile
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KDE Development with Podman
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.
nvidia-docker
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What are the best AI tools you've ACTUALLY used?
https://ubuntu.com/blog/getting-started-with-cuda-on-ubuntu-on-wsl-2 https://docs.nvidia.com/cuda/wsl-user-guide/index.html https://github.com/NVIDIA/nvidia-docker https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&Distribution=WSL-Ubuntu&target_version=2.0&target_type=deb_local
Nvidia Docker on GitHub
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Plex setup through Docker + Nvidia card, but hardware acceleration stops working after some time
Here's where I found discussion regarding this https://github.com/NVIDIA/nvidia-docker/issues/1671
I have sort of a weird problem. I've setup a Plex docker container with Nvidia HW acceleration and everything appears to be working (I used this https://github.com/NVIDIA/nvidia-docker and this https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/user-guide.html to set it up, using the latest LSIO Docker image).
- [D] Would a Tesla M40 provide cheap inference acceleration for self-hosted LLMs?
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Your own Stable Diffusion endpoint with AWS SageMaker
For my local computer, I used nvidia-docker to allow myself to run the code inside a container. This way I don't have to worry about installing the right version of CUDA (relative to pytorch) on my machine.
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A Web UI for Stable Diffusion
There's some trickery and some details, but yes: https://github.com/NVIDIA/nvidia-docker
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Setup my first Plex server, and used Docker for the first time and this is what I've achieved! Is there anything I've missed?
If you're going to make your plex server available to others outside your network, you're likely going to be transcoding the streams. If you were planning on using an Nvidia gpu, you'll need this to give your plex container access to your gpu.
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GPU in a VM in Docker
like the guy below said, you also need to installed the nvidia runtime for docker https://github.com/NVIDIA/nvidia-docker
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Is Debian 10 Alright to use? Or should I upgrade to 11???
Although... It looks like they are close to getting it working https://github.com/NVIDIA/nvidia-docker/issues/1549
What are some alternatives?
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
nvidia-container-runtime - NVIDIA container runtime
Entware - Ultimate repo for embedded devices
zed-docker - Docker images for the ZED SDK
Whisparr
docker-to-linux - Make bootable Linux disk image abusing Docker
jetson-containers - Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
zed-ros2-wrapper - ROS 2 wrapper for the ZED SDK
Plex-Meta-Manager - Python script to update metadata information for items in plex as well as automatically build collections and playlists. The Wiki Documentation is linked below.
CommunityGrid - VCC Community Grid at Dallas Makerspace
docker-languagetool - Dockerfile for LanguageTool
docker-languagetool - Dockerfile for LanguageTool server - configurable