185 lines
		
	
	
		
			6.8 KiB
		
	
	
	
		
			Docker
		
	
	
	
			
		
		
	
	
			185 lines
		
	
	
		
			6.8 KiB
		
	
	
	
		
			Docker
		
	
	
	
ARG NVIDIA_IMAGE=nvcr.io/nvidia/tensorflow:22.12-tf2-py3
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FROM ${NVIDIA_IMAGE}
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#### copied from https://github.com/jupyter/docker-stacks/tree/main/docker-stacks-foundation
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# Copyright (c) Jupyter Development Team.
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# Distributed under the terms of the Modified BSD License.
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# Ubuntu 22.04 (jammy)
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# https://hub.docker.com/_/ubuntu/tags?page=1&name=jammy
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ARG ROOT_CONTAINER=ubuntu:22.04
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LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
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ARG NB_USER="jovyan"
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ARG NB_UID="1000"
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ARG NB_GID="100"
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# Fix: https://github.com/hadolint/hadolint/wiki/DL4006
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# Fix: https://github.com/koalaman/shellcheck/wiki/SC3014
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SHELL ["/bin/bash", "-o", "pipefail", "-c"]
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USER root
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# Install all OS dependencies for notebook server that starts but lacks all
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# features (e.g., download as all possible file formats)
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ENV DEBIAN_FRONTEND noninteractive
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RUN apt-get update --yes && \
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    # - apt-get upgrade is run to patch known vulnerabilities in apt-get packages as
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    #   the ubuntu base image is rebuilt too seldom sometimes (less than once a month)
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    apt-get upgrade --yes && \
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    apt-get install --yes --no-install-recommends \
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    # - bzip2 is necessary to extract the micromamba executable.
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    bzip2 \
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    ca-certificates \
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    locales \
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    sudo \
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    # - tini is installed as a helpful container entrypoint that reaps zombie
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    #   processes and such of the actual executable we want to start, see
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    #   https://github.com/krallin/tini#why-tini for details.
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    tini \
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    wget && \
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    apt-get clean && rm -rf /var/lib/apt/lists/* && \
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    echo "en_US.UTF-8 UTF-8" > /etc/locale.gen && \
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    locale-gen
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# Configure environment
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ENV CONDA_DIR=/opt/conda \
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    SHELL=/bin/bash \
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    NB_USER="${NB_USER}" \
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    NB_UID=${NB_UID} \
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    NB_GID=${NB_GID} \
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    LC_ALL=en_US.UTF-8 \
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    LANG=en_US.UTF-8 \
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    LANGUAGE=en_US.UTF-8
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ENV PATH="${CONDA_DIR}/bin:${PATH}" \
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    HOME="/home/${NB_USER}"
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# Copy a script that we will use to correct permissions after running certain commands
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COPY fix-permissions /usr/local/bin/fix-permissions
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RUN chmod a+rx /usr/local/bin/fix-permissions
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# Enable prompt color in the skeleton .bashrc before creating the default NB_USER
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# hadolint ignore=SC2016
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RUN sed -i 's/^#force_color_prompt=yes/force_color_prompt=yes/' /etc/skel/.bashrc && \
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   # Add call to conda init script see https://stackoverflow.com/a/58081608/4413446
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   echo 'eval "$(command conda shell.bash hook 2> /dev/null)"' >> /etc/skel/.bashrc
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# Create NB_USER with name jovyan user with UID=1000 and in the 'users' group
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# and make sure these dirs are writable by the `users` group.
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RUN echo "auth requisite pam_deny.so" >> /etc/pam.d/su && \
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    sed -i.bak -e 's/^%admin/#%admin/' /etc/sudoers && \
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    sed -i.bak -e 's/^%sudo/#%sudo/' /etc/sudoers && \
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    useradd -l -m -s /bin/bash -N -u "${NB_UID}" "${NB_USER}" && \
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    mkdir -p "${CONDA_DIR}" && \
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    chown "${NB_USER}:${NB_GID}" "${CONDA_DIR}" && \
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    chmod g+w /etc/passwd && \
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    fix-permissions "${HOME}" && \
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    fix-permissions "${CONDA_DIR}"
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USER ${NB_UID}
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# Pin python version here, or set it to "default"
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ARG PYTHON_VERSION=3.10
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# Setup work directory for backward-compatibility
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RUN mkdir "/home/${NB_USER}/work" && \
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    fix-permissions "/home/${NB_USER}"
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# Download and install Micromamba, and initialize Conda prefix.
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#   <https://github.com/mamba-org/mamba#micromamba>
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#   Similar projects using Micromamba:
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#     - Micromamba-Docker: <https://github.com/mamba-org/micromamba-docker>
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#     - repo2docker: <https://github.com/jupyterhub/repo2docker>
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# Install Python, Mamba and jupyter_core
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# Cleanup temporary files and remove Micromamba
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# Correct permissions
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# Do all this in a single RUN command to avoid duplicating all of the
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# files across image layers when the permissions change
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COPY --chown="${NB_UID}:${NB_GID}" ./initial-condarc "${CONDA_DIR}/.condarc"
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WORKDIR /tmp
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RUN set -x && \
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    arch=$(uname -m) && \
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    if [ "${arch}" = "x86_64" ]; then \
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        # Should be simpler, see <https://github.com/mamba-org/mamba/issues/1437>
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        arch="64"; \
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    fi && \
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    wget -qO /tmp/micromamba.tar.bz2 \
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        "https://micromamba.snakepit.net/api/micromamba/linux-${arch}/latest" && \
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    tar -xvjf /tmp/micromamba.tar.bz2 --strip-components=1 bin/micromamba && \
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    rm /tmp/micromamba.tar.bz2 && \
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    PYTHON_SPECIFIER="python=${PYTHON_VERSION}" && \
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    if [[ "${PYTHON_VERSION}" == "default" ]]; then PYTHON_SPECIFIER="python"; fi && \
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    # Install the packages
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    ./micromamba install \
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        --root-prefix="${CONDA_DIR}" \
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        --prefix="${CONDA_DIR}" \
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        --yes \
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        "${PYTHON_SPECIFIER}" \
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        'mamba' \
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        'jupyter_core' && \
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    rm micromamba && \
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    # Pin major.minor version of python
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    mamba list python | grep '^python ' | tr -s ' ' | cut -d ' ' -f 1,2 >> "${CONDA_DIR}/conda-meta/pinned" && \
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    mamba clean --all -f -y && \
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    fix-permissions "${CONDA_DIR}" && \
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    fix-permissions "/home/${NB_USER}"
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# Configure container startup
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ENTRYPOINT ["tini", "-g", "--"]
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CMD ["start.sh"]
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# Copy local files as late as possible to avoid cache busting
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COPY start.sh /usr/local/bin/
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# Switch back to jovyan to avoid accidental container runs as root
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USER ${NB_UID}
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WORKDIR "${HOME}"
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################ copied from https://github.com/iot-salzburg/gpu-jupyter/tree/master/src
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# LABEL authors="Christoph Schranz <christoph.schranz@salzburgresearch.at>, Mathematical Michael <consistentbayes@gmail.com>"
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# Install Tensorflow, check compatibility here:
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# https://www.tensorflow.org/install/source#gpu
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# installation via conda leads to errors in version 4.8.2
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RUN pip install --upgrade pip && \
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    pip install --no-cache-dir "tensorflow==2.10.1"
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RUN pip install --upgrade pip && \
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    pip install --no-cache-dir keras==2.11.0
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# Install PyTorch with dependencies
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RUN conda install --quiet --yes \
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    pyyaml mkl mkl-include setuptools cmake cffi typing && \
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    conda clean --all -f -y && \
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    fix-permissions $CONDA_DIR && \
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    fix-permissions /home/$NB_USER
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# Check compatibility here:
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# https://pytorch.org/get-started/locally/
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# Installation via conda leads to errors installing cudatoolkit=11.1
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RUN pip install --no-cache-dir torch torchvision torchaudio torchviz --extra-index-url https://download.pytorch.org/whl/cu116
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ENV CUDA_PATH=/opt/conda/
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USER root
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# Install nvtop to monitor the gpu tasks
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RUN apt-get update && \
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    apt-get install -y cmake libncurses5-dev libncursesw5-dev git && \
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    rm -rf /var/lib/apt/lists/*
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RUN git clone https://github.com/Syllo/nvtop.git /run/nvtop && \
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    mkdir -p /run/nvtop/build && cd /run/nvtop/build && \
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    (cmake .. -DNVML_RETRIEVE_HEADER_ONLINE=True 2> /dev/null || echo "cmake was not successful") && \
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    (make 2> /dev/null || echo "make was not successful") && \
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    (make install 2> /dev/null || echo "make install was not successful") && \
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    cd /tmp && rm -rf /tmp/nvtop
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RUN fix-permissions /home/$NB_USER
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USER $NB_UID |