dclong/jupyterhub-pytorch @DockerHub | @GitHub

JupyterHub with PyTorch (GPU/CUDA enabled) in Docker.

Prerequisite

You need to install Docker before you use this Docker image.

Usage in Linux/Unix

Please refer to the Section Usage of the post My Docker Images for detailed instruction on how to use the Docker image.

The following command starts a container and mounts the current working directory and /home on the host machine to /workdir and /home_host in the container respectively.

docker run -d --init \
    --platform linux/amd64 \
    --hostname jupyterhub-pytorch \
    --log-opt max-size=50m \
    -p 8000:8000 \
    --gpus all \
    -e DOCKER_USER=$(id -un) \
    -e DOCKER_USER_ID=$(id -u) \
    -e DOCKER_PASSWORD=$(id -un) \
    -e DOCKER_GROUP_ID=$(id -g) \
    -v "$(pwd)":/workdir \
    -v "$(dirname $HOME)":/home_host \
    dclong/jupyterhub-pytorch /scripts/sys/init.sh

The following command (only works on Linux) does the same as the above one except that it limits the use of CPU and memory.

docker run -d --init \
    --platform linux/amd64 \
    --hostname jupyterhub-pytorch \
    --log-opt max-size=50m \
    --memory=$(($(head -n 1 /proc/meminfo | awk '{print $2}') * 4 / 5))k \
    --cpus=$(($(nproc) - 1)) \
    -p 8000:8000 \
    --gpus all \
    -e DOCKER_USER=$(id -un) \
    -e DOCKER_USER_ID=$(id -u) \
    -e DOCKER_PASSWORD=$(id -un) \
    -e DOCKER_GROUP_ID=$(id -g) \
    -v "$(pwd)":/workdir \
    -v "$(dirname $HOME)":/home_host \
    dclong/jupyterhub-pytorch /scripts/sys/init.sh

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