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feature: set sparse Dockerfile with Python interpreter only

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This commit is contained in:
Christoph Schranz 2020-06-22 13:26:01 +02:00
parent da9c98689e
commit a4d5573698
10 changed files with 232 additions and 318 deletions
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258
.build/Dockerfile
View File

@ -2,7 +2,7 @@
# The version of cudatoolkit must match those of the base image, see Dockerfile.pytorch # The version of cudatoolkit must match those of the base image, see Dockerfile.pytorch
FROM nvidia/cuda:10.1-base-ubuntu18.04 FROM nvidia/cuda:10.1-base-ubuntu18.04
LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>" LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
# The maintainers of subsequent sections may vary # This is a concatenated Dockerfile, the maintainers of subsequent sections may vary.
############################################################################ ############################################################################
#################### Dependency: jupyter/base-image ######################## #################### Dependency: jupyter/base-image ########################
@ -11,15 +11,19 @@ LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
# Copyright (c) Jupyter Development Team. # Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License. # Distributed under the terms of the Modified BSD License.
# Ubuntu 18.04 (bionic) # Ubuntu 20.04 (focal)
# https://hub.docker.com/_/ubuntu/?tab=tags&name=bionic # https://hub.docker.com/_/ubuntu/?tab=tags&name=focal
ARG ROOT_CONTAINER=ubuntu:bionic-20200112@sha256:bc025862c3e8ec4a8754ea4756e33da6c41cba38330d7e324abd25c8e0b93300 # OS/ARCH: linux/amd64
ARG ROOT_CONTAINER=ubuntu:focal-20200423@sha256:238e696992ba9913d24cfc3727034985abd136e08ee3067982401acdc30cbf3f
LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>" LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
ARG NB_USER="jovyan" ARG NB_USER="jovyan"
ARG NB_UID="1000" ARG NB_UID="1000"
ARG NB_GID="100" ARG NB_GID="100"
# Fix DL4006
SHELL ["/bin/bash", "-o", "pipefail", "-c"]
USER root USER root
# Install all OS dependencies for notebook server that starts but lacks all # Install all OS dependencies for notebook server that starts but lacks all
@ -68,7 +72,7 @@ RUN echo "auth requisite pam_deny.so" >> /etc/pam.d/su && \
chown $NB_USER:$NB_GID $CONDA_DIR && \ chown $NB_USER:$NB_GID $CONDA_DIR && \
chmod g+w /etc/passwd && \ chmod g+w /etc/passwd && \
fix-permissions $HOME && \ fix-permissions $HOME && \
fix-permissions "$(dirname $CONDA_DIR)" fix-permissions $CONDA_DIR
USER $NB_UID USER $NB_UID
WORKDIR $HOME WORKDIR $HOME
@ -79,19 +83,20 @@ RUN mkdir /home/$NB_USER/work && \
fix-permissions /home/$NB_USER fix-permissions /home/$NB_USER
# Install conda as jovyan and check the md5 sum provided on the download site # Install conda as jovyan and check the md5 sum provided on the download site
ENV MINICONDA_VERSION=4.7.12.1 \ ENV MINICONDA_VERSION=4.8.2 \
MINICONDA_MD5=81c773ff87af5cfac79ab862942ab6b3 \ MINICONDA_MD5=87e77f097f6ebb5127c77662dfc3165e \
CONDA_VERSION=4.7.12 CONDA_VERSION=4.8.2
RUN cd /tmp && \ WORKDIR /tmp
wget --quiet https://repo.continuum.io/miniconda/Miniconda3-${MINICONDA_VERSION}-Linux-x86_64.sh && \ RUN wget --quiet https://repo.continuum.io/miniconda/Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh && \
echo "${MINICONDA_MD5} *Miniconda3-${MINICONDA_VERSION}-Linux-x86_64.sh" | md5sum -c - && \ echo "${MINICONDA_MD5} *Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh" | md5sum -c - && \
/bin/bash Miniconda3-${MINICONDA_VERSION}-Linux-x86_64.sh -f -b -p $CONDA_DIR && \ /bin/bash Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh -f -b -p $CONDA_DIR && \
rm Miniconda3-${MINICONDA_VERSION}-Linux-x86_64.sh && \ rm Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh && \
echo "conda ${CONDA_VERSION}" >> $CONDA_DIR/conda-meta/pinned && \ echo "conda ${CONDA_VERSION}" >> $CONDA_DIR/conda-meta/pinned && \
conda config --system --prepend channels conda-forge && \ conda config --system --prepend channels conda-forge && \
conda config --system --set auto_update_conda false && \ conda config --system --set auto_update_conda false && \
conda config --system --set show_channel_urls true && \ conda config --system --set show_channel_urls true && \
conda config --system --set channel_priority strict && \
if [ ! $PYTHON_VERSION = 'default' ]; then conda install --yes python=$PYTHON_VERSION; fi && \ if [ ! $PYTHON_VERSION = 'default' ]; then conda install --yes python=$PYTHON_VERSION; fi && \
conda list python | grep '^python ' | tr -s ' ' | cut -d '.' -f 1,2 | sed 's/$/.*/' >> $CONDA_DIR/conda-meta/pinned && \ conda list python | grep '^python ' | tr -s ' ' | cut -d '.' -f 1,2 | sed 's/$/.*/' >> $CONDA_DIR/conda-meta/pinned && \
conda install --quiet --yes conda && \ conda install --quiet --yes conda && \
@ -118,7 +123,7 @@ RUN conda install --quiet --yes 'tini=0.18.0' && \
RUN conda install --quiet --yes \ RUN conda install --quiet --yes \
'notebook=6.0.3' \ 'notebook=6.0.3' \
'jupyterhub=1.1.0' \ 'jupyterhub=1.1.0' \
'jupyterlab=1.2.5' && \ 'jupyterlab=2.1.3' && \
conda clean --all -f -y && \ conda clean --all -f -y && \
npm cache clean --force && \ npm cache clean --force && \
jupyter notebook --generate-config && \ jupyter notebook --generate-config && \
@ -134,9 +139,7 @@ ENTRYPOINT ["tini", "-g", "--"]
CMD ["start-notebook.sh"] CMD ["start-notebook.sh"]
# Copy local files as late as possible to avoid cache busting # Copy local files as late as possible to avoid cache busting
COPY start.sh /usr/local/bin/ COPY start.sh start-notebook.sh start-singleuser.sh /usr/local/bin/
COPY start-notebook.sh /usr/local/bin/
COPY start-singleuser.sh /usr/local/bin/
COPY jupyter_notebook_config.py /etc/jupyter/ COPY jupyter_notebook_config.py /etc/jupyter/
# Fix permissions on /etc/jupyter as root # Fix permissions on /etc/jupyter as root
@ -146,6 +149,8 @@ RUN fix-permissions /etc/jupyter/
# Switch back to jovyan to avoid accidental container runs as root # Switch back to jovyan to avoid accidental container runs as root
USER $NB_UID USER $NB_UID
WORKDIR $HOME
############################################################################ ############################################################################
################# Dependency: jupyter/minimal-notebook ##################### ################# Dependency: jupyter/minimal-notebook #####################
############################################################################ ############################################################################
@ -160,7 +165,8 @@ USER root
# Install all OS dependencies for fully functional notebook server # Install all OS dependencies for fully functional notebook server
RUN apt-get update && apt-get install -yq --no-install-recommends \ RUN apt-get update && apt-get install -yq --no-install-recommends \
build-essential \ build-essential \
emacs \ emacs-nox \
vim-tiny \
git \ git \
inkscape \ inkscape \
jed \ jed \
@ -173,7 +179,7 @@ RUN apt-get update && apt-get install -yq --no-install-recommends \
# ---- nbconvert dependencies ---- # ---- nbconvert dependencies ----
texlive-xetex \ texlive-xetex \
texlive-fonts-recommended \ texlive-fonts-recommended \
texlive-generic-recommended \ texlive-plain-generic \
# Optional dependency # Optional dependency
texlive-fonts-extra \ texlive-fonts-extra \
# ---- # ----
@ -196,40 +202,45 @@ LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
USER root USER root
# ffmpeg for matplotlib anim # ffmpeg for matplotlib anim & dvipng for latex labels
RUN apt-get update && \ RUN apt-get update && \
apt-get install -y --no-install-recommends ffmpeg && \ apt-get install -y --no-install-recommends ffmpeg dvipng && \
rm -rf /var/lib/apt/lists/* rm -rf /var/lib/apt/lists/*
USER $NB_UID USER $NB_UID
# Install Python 3 packages # Install Python 3 packages
RUN conda install --quiet --yes \ RUN conda install --quiet --yes \
'beautifulsoup4=4.8.*' \ 'beautifulsoup4=4.9.*' \
'conda-forge::blas=*=openblas' \ 'conda-forge::blas=*=openblas' \
'bokeh=1.4.*' \ 'bokeh=2.0.*' \
'cloudpickle=1.2.*' \ 'bottleneck=1.3.*' \
'cloudpickle=1.4.*' \
'cython=0.29.*' \ 'cython=0.29.*' \
'dask=2.9.*' \ 'dask=2.15.*' \
'dill=0.3.*' \ 'dill=0.3.*' \
'h5py=2.10.*' \ 'h5py=2.10.*' \
'hdf5=1.10.*' \ 'hdf5=1.10.*' \
'ipywidgets=7.5.*' \ 'ipywidgets=7.5.*' \
'matplotlib-base=3.1.*' \ 'ipympl=0.5.*'\
'matplotlib-base=3.2.*' \
# numba update to 0.49 fails resolving deps.
'numba=0.48.*' \ 'numba=0.48.*' \
'numexpr=2.7.*' \ 'numexpr=2.7.*' \
'pandas=0.25.*' \ 'pandas=1.0.*' \
'patsy=0.5.*' \ 'patsy=0.5.*' \
'protobuf=3.11.*' \ 'protobuf=3.11.*' \
'pytables=3.6.*' \
'scikit-image=0.16.*' \ 'scikit-image=0.16.*' \
'scikit-learn=0.22.*' \ 'scikit-learn=0.22.*' \
'scipy=1.4.*' \ 'scipy=1.4.*' \
'seaborn=0.9.*' \ 'seaborn=0.10.*' \
'sqlalchemy=1.3.*' \ 'sqlalchemy=1.3.*' \
'statsmodels=0.11.*' \ 'statsmodels=0.11.*' \
'sympy=1.5.*' \ 'sympy=1.5.*' \
'vincent=0.4.*' \ 'vincent=0.4.*' \
'xlrd' \ 'widgetsnbextension=3.5.*'\
'xlrd=1.2.*' \
&& \ && \
conda clean --all -f -y && \ conda clean --all -f -y && \
# Activate ipywidgets extension in the environment that runs the notebook server # Activate ipywidgets extension in the environment that runs the notebook server
@ -237,121 +248,34 @@ RUN conda install --quiet --yes \
# Also activate ipywidgets extension for JupyterLab # Also activate ipywidgets extension for JupyterLab
# Check this URL for most recent compatibilities # Check this URL for most recent compatibilities
# https://github.com/jupyter-widgets/ipywidgets/tree/master/packages/jupyterlab-manager # https://github.com/jupyter-widgets/ipywidgets/tree/master/packages/jupyterlab-manager
jupyter labextension install @jupyter-widgets/jupyterlab-manager@^1.0.1 --no-build && \ jupyter labextension install @jupyter-widgets/jupyterlab-manager@^2.0.0 --no-build && \
jupyter labextension install jupyterlab_bokeh@1.0.0 --no-build && \ jupyter labextension install @bokeh/jupyter_bokeh@^2.0.0 --no-build && \
jupyter lab build && \ jupyter labextension install jupyter-matplotlib@^0.7.2 --no-build && \
jupyter lab build -y && \
jupyter lab clean -y && \
npm cache clean --force && \ npm cache clean --force && \
rm -rf $CONDA_DIR/share/jupyter/lab/staging && \ rm -rf "/home/${NB_USER}/.cache/yarn" && \
rm -rf /home/$NB_USER/.cache/yarn && \ rm -rf "/home/${NB_USER}/.node-gyp" && \
rm -rf /home/$NB_USER/.node-gyp && \ fix-permissions "${CONDA_DIR}" && \
fix-permissions $CONDA_DIR && \ fix-permissions "/home/${NB_USER}"
fix-permissions /home/$NB_USER
# Install facets which does not have a pip or conda package at the moment # Install facets which does not have a pip or conda package at the moment
RUN cd /tmp && \ WORKDIR /tmp
git clone https://github.com/PAIR-code/facets.git && \ RUN git clone https://github.com/PAIR-code/facets.git && \
cd facets && \ jupyter nbextension install facets/facets-dist/ --sys-prefix && \
jupyter nbextension install facets-dist/ --sys-prefix && \
cd && \
rm -rf /tmp/facets && \ rm -rf /tmp/facets && \
fix-permissions $CONDA_DIR && \ fix-permissions "${CONDA_DIR}" && \
fix-permissions /home/$NB_USER fix-permissions "/home/${NB_USER}"
# Import matplotlib the first time to build the font cache. # Import matplotlib the first time to build the font cache.
ENV XDG_CACHE_HOME /home/$NB_USER/.cache/ ENV XDG_CACHE_HOME="/home/${NB_USER}/.cache/"
RUN MPLBACKEND=Agg python -c "import matplotlib.pyplot" && \ RUN MPLBACKEND=Agg python -c "import matplotlib.pyplot" && \
fix-permissions /home/$NB_USER fix-permissions "/home/${NB_USER}"
USER $NB_UID USER $NB_UID
############################################################################ WORKDIR $HOME
################ Dependency: jupyter/datascience-notebook ##################
############################################################################
# Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License.
LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
# Set when building on Travis so that certain long-running build steps can
# be skipped to shorten build time.
ARG TEST_ONLY_BUILD
USER root
# R pre-requisites
RUN apt-get update && \
apt-get install -y --no-install-recommends \
fonts-dejavu \
gfortran \
gcc && \
rm -rf /var/lib/apt/lists/*
# Julia dependencies
# install Julia packages in /opt/julia instead of $HOME
ENV JULIA_DEPOT_PATH=/opt/julia
ENV JULIA_PKGDIR=/opt/julia
ENV JULIA_VERSION=1.3.1
RUN mkdir /opt/julia-${JULIA_VERSION} && \
cd /tmp && \
wget -q https://julialang-s3.julialang.org/bin/linux/x64/`echo ${JULIA_VERSION} | cut -d. -f 1,2`/julia-${JULIA_VERSION}-linux-x86_64.tar.gz && \
echo "faa707c8343780a6fe5eaf13490355e8190acf8e2c189b9e7ecbddb0fa2643ad *julia-${JULIA_VERSION}-linux-x86_64.tar.gz" | sha256sum -c - && \
tar xzf julia-${JULIA_VERSION}-linux-x86_64.tar.gz -C /opt/julia-${JULIA_VERSION} --strip-components=1 && \
rm /tmp/julia-${JULIA_VERSION}-linux-x86_64.tar.gz
RUN ln -fs /opt/julia-*/bin/julia /usr/local/bin/julia
# Show Julia where conda libraries are \
RUN mkdir /etc/julia && \
echo "push!(Libdl.DL_LOAD_PATH, \"$CONDA_DIR/lib\")" >> /etc/julia/juliarc.jl && \
# Create JULIA_PKGDIR \
mkdir $JULIA_PKGDIR && \
chown $NB_USER $JULIA_PKGDIR && \
fix-permissions $JULIA_PKGDIR
USER $NB_UID
# R packages including IRKernel which gets installed globally.
RUN conda install --quiet --yes \
'r-base=3.6.2' \
'r-caret=6.0*' \
'r-crayon=1.3*' \
'r-devtools=2.2*' \
'r-forecast=8.10*' \
'r-hexbin=1.28*' \
'r-htmltools=0.4*' \
'r-htmlwidgets=1.5*' \
'r-irkernel=1.1*' \
'r-nycflights13=1.0*' \
'r-plyr=1.8*' \
'r-randomforest=4.6*' \
'r-rcurl=1.98*' \
'r-reshape2=1.4*' \
'r-rmarkdown=2.1*' \
'r-rsqlite=2.1*' \
'r-shiny=1.3*' \
'r-tidyverse=1.3*' \
'rpy2=3.1*' \
&& \
conda clean --all -f -y && \
fix-permissions $CONDA_DIR && \
fix-permissions /home/$NB_USER
# Add Julia packages. Only add HDF5 if this is not a test-only build since
# it takes roughly half the entire build time of all of the images on Travis
# to add this one package and often causes Travis to timeout.
#
# Install IJulia as jovyan and then move the kernelspec out
# to the system share location. Avoids problems with runtime UID change not
# taking effect properly on the .local folder in the jovyan home dir.
RUN julia -e 'import Pkg; Pkg.update()' && \
(test $TEST_ONLY_BUILD || julia -e 'import Pkg; Pkg.add("HDF5")') && \
julia -e "using Pkg; pkg\"add IJulia\"; pkg\"precompile\"" && \
# move kernelspec out of home \
mv $HOME/.local/share/jupyter/kernels/julia* $CONDA_DIR/share/jupyter/kernels/ && \
chmod -R go+rx $CONDA_DIR/share/jupyter && \
rm -rf $HOME/.local && \
fix-permissions $JULIA_PKGDIR $CONDA_DIR/share/jupyter
############################################################################ ############################################################################
########################## Dependency: gpulibs ############################# ########################## Dependency: gpulibs #############################
@ -360,11 +284,15 @@ RUN julia -e 'import Pkg; Pkg.update()' && \
LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>" LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
# Install Tensorflow, check compatibility here: https://www.tensorflow.org/install/gpu # Install Tensorflow, check compatibility here: https://www.tensorflow.org/install/gpu
RUN conda install --quiet --yes \ # installation via conda leads to errors in version 4.8.2
'tensorflow-gpu=2.1*' \ #RUN conda install --quiet --yes \
'keras-gpu' && \ # 'tensorflow-gpu=2.1*' \
fix-permissions $CONDA_DIR && \ # 'keras-gpu' && \
fix-permissions /home/$NB_USER # fix-permissions $CONDA_DIR && \
# fix-permissions /home/$NB_USER
RUN pip install --upgrade pip && \
pip install --no-cache-dir "tensorflow-gpu>=2.1.*" && \
pip install --no-cache-dir keras
# Install PyTorch with dependencies # Install PyTorch with dependencies
RUN conda install --quiet --yes \ RUN conda install --quiet --yes \
@ -382,57 +310,5 @@ RUN conda clean --all -f -y && \
fix-permissions $CONDA_DIR && \ fix-permissions $CONDA_DIR && \
fix-permissions /home/$NB_USER fix-permissions /home/$NB_USER
############################################################################
############################ Useful packages ###############################
############################################################################
LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
# Update conda
RUN conda update -n base conda -y
USER root
# Install elasticsearch libs
USER root
RUN apt-get update \
&& curl -sL https://repo1.maven.org/maven2/org/elasticsearch/elasticsearch-hadoop/6.8.1/elasticsearch-hadoop-6.8.1.jar
RUN pip install --no-cache-dir elasticsearch==7.1.0
# Install rpy2 to share data between Python and R
RUN conda install rpy2=2.9.4 plotly=4.4.1
RUN conda install -c conda-forge ipyleaflet
# Install important packages and Graphviz
RUN set -ex \
&& buildDeps=' \
graphviz==0.11 \
' \
&& apt-get update \
&& apt-get -y install htop apt-utils graphviz libgraphviz-dev \
&& pip install --no-cache-dir $buildDeps
# Install various extensions
RUN jupyter labextension install @jupyterlab/github
RUN jupyter labextension install jupyterlab-drawio
RUN jupyter labextension install jupyter-leaflet
RUN jupyter labextension install @jupyterlab/plotly-extension
RUN jupyter labextension install @jupyter-widgets/jupyterlab-manager
RUN pip install --no-cache-dir jupyter-tabnine==1.0.2 && \
jupyter nbextension install --py jupyter_tabnine && \
jupyter nbextension enable --py jupyter_tabnine && \
jupyter serverextension enable --py jupyter_tabnine
RUN fix-permissions $CONDA_DIR
RUN conda install -c conda-forge jupyter_contrib_nbextensions && \
conda install -c conda-forge jupyter_nbextensions_configurator && \
conda install -c conda-forge rise && \
jupyter nbextension enable codefolding/main
RUN jupyter labextension install @ijmbarr/jupyterlab_spellchecker
RUN fix-permissions /home/$NB_USER
# Switch back to jovyan to avoid accidental container runs as root
USER $NB_UID
# Copy jupyter_notebook_config.json # Copy jupyter_notebook_config.json
COPY jupyter_notebook_config.json /etc/jupyter/ COPY jupyter_notebook_config.json /etc/jupyter/

2
.build/docker-stacks

@ -1 +1 @@
Subproject commit c1c32938438151c7e2a22b5aa338caba2ec01da2 Subproject commit 04f7f60d34a674a2964d96a6cb97c57a7870a828

10
.build/start-notebook.sh
View File

@ -6,14 +6,14 @@ set -e
wrapper="" wrapper=""
if [[ "${RESTARTABLE}" == "yes" ]]; then if [[ "${RESTARTABLE}" == "yes" ]]; then
wrapper="run-one-constantly" wrapper="run-one-constantly"
fi fi
if [[ ! -z "${JUPYTERHUB_API_TOKEN}" ]]; then if [[ ! -z "${JUPYTERHUB_API_TOKEN}" ]]; then
# launched by JupyterHub, use single-user entrypoint # launched by JupyterHub, use single-user entrypoint
exec /usr/local/bin/start-singleuser.sh "$@" exec /usr/local/bin/start-singleuser.sh "$@"
elif [[ ! -z "${JUPYTER_ENABLE_LAB}" ]]; then elif [[ ! -z "${JUPYTER_ENABLE_LAB}" ]]; then
. /usr/local/bin/start.sh $wrapper jupyter lab "$@" . /usr/local/bin/start.sh $wrapper jupyter lab "$@"
else else
. /usr/local/bin/start.sh $wrapper jupyter notebook "$@" . /usr/local/bin/start.sh $wrapper jupyter notebook "$@"
fi fi

22
.build/start-singleuser.sh
View File

@ -6,7 +6,7 @@ set -e
# set default ip to 0.0.0.0 # set default ip to 0.0.0.0
if [[ "$NOTEBOOK_ARGS $@" != *"--ip="* ]]; then if [[ "$NOTEBOOK_ARGS $@" != *"--ip="* ]]; then
NOTEBOOK_ARGS="--ip=0.0.0.0 $NOTEBOOK_ARGS" NOTEBOOK_ARGS="--ip=0.0.0.0 $NOTEBOOK_ARGS"
fi fi
# handle some deprecated environment variables # handle some deprecated environment variables
@ -14,30 +14,26 @@ fi
# These won't be passed from DockerSpawner 0.9, # These won't be passed from DockerSpawner 0.9,
# so avoid specifying --arg=empty-string # so avoid specifying --arg=empty-string
if [ ! -z "$NOTEBOOK_DIR" ]; then if [ ! -z "$NOTEBOOK_DIR" ]; then
NOTEBOOK_ARGS="--notebook-dir='$NOTEBOOK_DIR' $NOTEBOOK_ARGS" NOTEBOOK_ARGS="--notebook-dir='$NOTEBOOK_DIR' $NOTEBOOK_ARGS"
fi fi
if [ ! -z "$JPY_PORT" ]; then if [ ! -z "$JPY_PORT" ]; then
NOTEBOOK_ARGS="--port=$JPY_PORT $NOTEBOOK_ARGS" NOTEBOOK_ARGS="--port=$JPY_PORT $NOTEBOOK_ARGS"
fi fi
if [ ! -z "$JPY_USER" ]; then if [ ! -z "$JPY_USER" ]; then
NOTEBOOK_ARGS="--user=$JPY_USER $NOTEBOOK_ARGS" NOTEBOOK_ARGS="--user=$JPY_USER $NOTEBOOK_ARGS"
fi fi
if [ ! -z "$JPY_COOKIE_NAME" ]; then if [ ! -z "$JPY_COOKIE_NAME" ]; then
NOTEBOOK_ARGS="--cookie-name=$JPY_COOKIE_NAME $NOTEBOOK_ARGS" NOTEBOOK_ARGS="--cookie-name=$JPY_COOKIE_NAME $NOTEBOOK_ARGS"
fi fi
if [ ! -z "$JPY_BASE_URL" ]; then if [ ! -z "$JPY_BASE_URL" ]; then
NOTEBOOK_ARGS="--base-url=$JPY_BASE_URL $NOTEBOOK_ARGS" NOTEBOOK_ARGS="--base-url=$JPY_BASE_URL $NOTEBOOK_ARGS"
fi fi
if [ ! -z "$JPY_HUB_PREFIX" ]; then if [ ! -z "$JPY_HUB_PREFIX" ]; then
NOTEBOOK_ARGS="--hub-prefix=$JPY_HUB_PREFIX $NOTEBOOK_ARGS" NOTEBOOK_ARGS="--hub-prefix=$JPY_HUB_PREFIX $NOTEBOOK_ARGS"
fi fi
if [ ! -z "$JPY_HUB_API_URL" ]; then if [ ! -z "$JPY_HUB_API_URL" ]; then
NOTEBOOK_ARGS="--hub-api-url=$JPY_HUB_API_URL $NOTEBOOK_ARGS" NOTEBOOK_ARGS="--hub-api-url=$JPY_HUB_API_URL $NOTEBOOK_ARGS"
fi
if [ ! -z "$JUPYTER_ENABLE_LAB" ]; then
NOTEBOOK_BIN="jupyter labhub"
else
NOTEBOOK_BIN="jupyterhub-singleuser"
fi fi
NOTEBOOK_BIN="jupyterhub-singleuser"
. /usr/local/bin/start.sh $NOTEBOOK_BIN $NOTEBOOK_ARGS "$@" . /usr/local/bin/start.sh $NOTEBOOK_BIN $NOTEBOOK_ARGS "$@"

2
.build/start.sh
View File

@ -93,7 +93,7 @@ if [ $(id -u) == 0 ] ; then
fi fi
# Add $CONDA_DIR/bin to sudo secure_path # Add $CONDA_DIR/bin to sudo secure_path
sed -r "s#Defaults\s+secure_path=\"([^\"]+)\"#Defaults secure_path=\"\1:$CONDA_DIR/bin\"#" /etc/sudoers | grep secure_path > /etc/sudoers.d/path sed -r "s#Defaults\s+secure_path\s*=\s*\"?([^\"]+)\"?#Defaults secure_path=\"\1:$CONDA_DIR/bin\"#" /etc/sudoers | grep secure_path > /etc/sudoers.d/path
# Exec the command as NB_USER with the PATH and the rest of # Exec the command as NB_USER with the PATH and the rest of
# the environment preserved # the environment preserved

79
README.md
View File

@ -5,7 +5,7 @@
First of all, thanks to [docker-stacks](https://github.com/jupyter/docker-stacks) First of all, thanks to [docker-stacks](https://github.com/jupyter/docker-stacks)
for creating and maintaining a robost Python, R and Julia toolstack for Data Analytics/Science for creating and maintaining a robost Python, R and Julia toolstack for Data Analytics/Science
applications. This project uses the NVIDIA CUDA image as a basis image and installs their applications. This project uses the NVIDIA CUDA image as the base image and installs their
toolstack on top of it to enable GPU calculations in the Jupyter notebooks. toolstack on top of it to enable GPU calculations in the Jupyter notebooks.
The image of this repository is available on [Dockerhub](https://hub.docker.com/r/cschranz/gpu-jupyter). The image of this repository is available on [Dockerhub](https://hub.docker.com/r/cschranz/gpu-jupyter).
@ -21,13 +21,34 @@ The image of this repository is available on [Dockerhub](https://hub.docker.com/
## Requirements ## Requirements
1. Install [Docker](https://www.docker.com/community-edition#/download) version **1.10.0+** 1. A NVIDIA GPU
2. Install [Docker](https://www.docker.com/community-edition#/download) version **1.10.0+**
and [Docker Compose](https://docs.docker.com/compose/install/) version **1.6.0+**. and [Docker Compose](https://docs.docker.com/compose/install/) version **1.6.0+**.
2. A NVIDIA GPU 3. Get access to your GPU via CUDA drivers within Docker containers. Therfore, check out this
3. Get access to use your GPU via the CUDA drivers, check out this
[medium article](https://medium.com/@christoph.schranz/set-up-your-own-gpu-based-jupyterlab-e0d45fcacf43). [medium article](https://medium.com/@christoph.schranz/set-up-your-own-gpu-based-jupyterlab-e0d45fcacf43).
The CUDA toolkit is not required on the host system, as it will be deployed The CUDA toolkit is not required on the host system, as it will be deployed
in [NVIDIA-docker](https://github.com/NVIDIA/nvidia-docker). in [NVIDIA-docker](https://github.com/NVIDIA/nvidia-docker).
You can be sure that you can access your GPU within Docker,
if the command `docker run --runtime nvidia nvidia/cuda:10.1-base-ubuntu18.04 nvidia-smi`
returns a result similar to this one:
```bash
Mon Jun 22 09:06:28 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.82 Driver Version: 440.82 CUDA Version: 10.1 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 207... Off | 00000000:01:00.0 On | N/A |
| 0% 46C P8 9W / 215W | 424MiB / 7974MiB | 6% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
```
4. Clone the Repository or pull the image from 4. Clone the Repository or pull the image from
[Dockerhub](https://hub.docker.com/repository/docker/cschranz/gpu-jupyter): [Dockerhub](https://hub.docker.com/repository/docker/cschranz/gpu-jupyter):
```bash ```bash
@ -37,30 +58,46 @@ The image of this repository is available on [Dockerhub](https://hub.docker.com/
## Quickstart ## Quickstart
First of all, it is necessary to generate the `Dockerfile` based on the latest toolstack of First of all, it is necessary to generate the `Dockerfile` based on the
[hub.docker.com/u/jupyter](https://hub.docker.com/u/jupyter). [docker-stacks](https://github.com/jupyter/docker-stacks).
As soon as you have access to your GPU locally (it can be tested via a Tensorflow or PyTorch As soon as you have access to your GPU within Docker containers
directly on the host node), you can run these commands to start the jupyter notebook via (make sure the command `docker run --runtime nvidia nvidia/cuda:10.1-base-ubuntu18.04 nvidia-smi` shows your
docker-compose (internally): GPU statistics), you can generate a Dockerfile and build it via docker-compose.
The two commands will start *GPU-Jupyter* on [localhost:1234](http://localhost:1234) with the default
password `asdf`.
```bash ```bash
./generate-Dockerfile.sh ./generate-Dockerfile.sh
./start-local.sh -p 1234 # where -p stands for the port, default 8888
```
## Parameter
The script `generate-Dockerfile.sh` has multiple parameters:
* `-c|--commit`: specify a commit or `"latest"` for the `docker-stacks`, the default commit is a working one.
* `-s|--slim`: Generate a slim Dockerfile.
As some installations are not needed by everyone, there is the possibility to skip some installations
to reduce the size of the image.
Here the `docker-stack` `scipy-notebook` is used instead of `datascience-notebook` that comes with Julia and R.
Moreover, none of the packages within `src/Dockerfile.usefulpackages` is installed.
* `--no-datascience-notebook`: As the name suggests, the `docker-stack` `datascience-notebook` is not installed
on top of the `scipy-notebook`, but the packages within `src/Dockerfile.usefulpackages` are.
* `--no-useful-packages`: On top of the `docker-stack` `datascience-notebook`, the essential `gpulibs` are installed
but not the packages within `src/Dockerfile.usefulpackages`.
The script `start-local.sh` is a wrapper for a quick configuration of the underlying `docker-compose.yml`.
It is equal to these commands:
```bash
docker build -t gpu-jupyter .build/ docker build -t gpu-jupyter .build/
docker run -d -p [port]:8888 gpu-jupyter docker run -d -p [port]:8888 gpu-jupyter
``` ```
Alternatively, you can configure the environment in `docker-compose.yml` and run
this to deploy the `GPU-Jupyter` via docker-compose (under-the-hood):
```bash
./generate-Dockerfile.sh
./start-local.sh -p 8888 # where -p stands for the port of the service
```
Both options will run *GPU-Jupyter* by default on [localhost:8888](http://localhost:8888) with the default
password `asdf`.
## Tracing ## Tracing
With these commands we can see if everything worked well: With these commands we can see if everything worked well:

100
extra/Getting_Started/GPU-processing.ipynb
View File

@ -27,15 +27,15 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"Wed Mar 11 07:16:17 2020 \n", "Mon Jun 22 11:24:08 2020 \n",
"+-----------------------------------------------------------------------------+\n", "+-----------------------------------------------------------------------------+\n",
"| NVIDIA-SMI 440.48.02 Driver Version: 440.48.02 CUDA Version: 10.2 |\n", "| NVIDIA-SMI 440.82 Driver Version: 440.82 CUDA Version: 10.2 |\n",
"|-------------------------------+----------------------+----------------------+\n", "|-------------------------------+----------------------+----------------------+\n",
"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n", "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n", "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
"|===============================+======================+======================|\n", "|===============================+======================+======================|\n",
"| 0 GeForce RTX 207... Off | 00000000:01:00.0 Off | N/A |\n", "| 0 GeForce RTX 207... Off | 00000000:01:00.0 On | N/A |\n",
"| 0% 42C P8 1W / 215W | 1788MiB / 7974MiB | 0% Default |\n", "| 0% 49C P0 38W / 215W | 430MiB / 7974MiB | 5% Default |\n",
"+-------------------------------+----------------------+----------------------+\n", "+-------------------------------+----------------------+----------------------+\n",
" \n", " \n",
"+-----------------------------------------------------------------------------+\n", "+-----------------------------------------------------------------------------+\n",
@ -87,10 +87,7 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"WARNING:tensorflow:From <ipython-input-3-d1bfbb527297>:3: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.\n", "[PhysicalDevice(name='/physical_device:XLA_GPU:0', device_type='XLA_GPU')]\n"
"Instructions for updating:\n",
"Use `tf.config.list_physical_devices('GPU')` instead.\n",
"True\n"
] ]
}, },
{ {
@ -101,30 +98,20 @@
" memory_limit: 268435456\n", " memory_limit: 268435456\n",
" locality {\n", " locality {\n",
" }\n", " }\n",
" incarnation: 8034786465358909470,\n", " incarnation: 12436949185972503812,\n",
" name: \"/device:XLA_CPU:0\"\n", " name: \"/device:XLA_CPU:0\"\n",
" device_type: \"XLA_CPU\"\n", " device_type: \"XLA_CPU\"\n",
" memory_limit: 17179869184\n", " memory_limit: 17179869184\n",
" locality {\n", " locality {\n",
" }\n", " }\n",
" incarnation: 13772661904993777233\n", " incarnation: 9674938692146126962\n",
" physical_device_desc: \"device: XLA_CPU device\",\n", " physical_device_desc: \"device: XLA_CPU device\",\n",
" name: \"/device:GPU:0\"\n",
" device_type: \"GPU\"\n",
" memory_limit: 5480775680\n",
" locality {\n",
" bus_id: 1\n",
" links {\n",
" }\n",
" }\n",
" incarnation: 8336380964433791501\n",
" physical_device_desc: \"device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:01:00.0, compute capability: 7.5\",\n",
" name: \"/device:XLA_GPU:0\"\n", " name: \"/device:XLA_GPU:0\"\n",
" device_type: \"XLA_GPU\"\n", " device_type: \"XLA_GPU\"\n",
" memory_limit: 17179869184\n", " memory_limit: 17179869184\n",
" locality {\n", " locality {\n",
" }\n", " }\n",
" incarnation: 4817022749254415174\n", " incarnation: 7870544216044264725\n",
" physical_device_desc: \"device: XLA_GPU device\"]" " physical_device_desc: \"device: XLA_GPU device\"]"
] ]
}, },
@ -136,7 +123,7 @@
"source": [ "source": [
"import tensorflow as tf\n", "import tensorflow as tf\n",
"from tensorflow.python.client import device_lib\n", "from tensorflow.python.client import device_lib\n",
"print(tf.test.is_gpu_available(cuda_only=True))\n", "print(tf.config.list_physical_devices('XLA_GPU'))\n",
"device_lib.list_local_devices()" "device_lib.list_local_devices()"
] ]
}, },
@ -148,11 +135,11 @@
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"tensor([[0.1091, 0.0178, 0.2500],\n", "tensor([[0.0399, 0.1738, 0.2486],\n",
" [0.1409, 0.9612, 0.0325],\n", " [0.7464, 0.1461, 0.8991],\n",
" [0.8944, 0.3869, 0.9657],\n", " [0.7264, 0.9835, 0.8844],\n",
" [0.8131, 0.5454, 0.2587],\n", " [0.4544, 0.8331, 0.8435],\n",
" [0.6570, 0.0147, 0.1361]])" " [0.0109, 0.0689, 0.2997]])"
] ]
}, },
"execution_count": 4, "execution_count": 4,
@ -202,7 +189,7 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"248 ms ± 174 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" "276 ms ± 9.97 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
] ]
} }
], ],
@ -236,13 +223,13 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"78.2 ms ± 250 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" "82.1 ms ± 1.85 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
] ]
} }
], ],
"source": [ "source": [
"%%timeit\n", "%%timeit\n",
"# Calculate the projection matrix of x\n", "# Calculate the projection matrix of x on the CPU\n",
"H = x.mm( (x.t().mm(x)).inverse() ).mm(x.t())" "H = x.mm( (x.t().mm(x)).inverse() ).mm(x.t())"
] ]
}, },
@ -262,16 +249,16 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"tensor([[0.0962, 0.3125, 0.7327, 0.5982, 0.4624],\n", "tensor([[0.2854, 0.3384, 0.6473, 0.0433, 0.5640],\n",
" [0.4655, 0.4890, 0.9603, 0.4339, 0.0524],\n", " [0.3960, 0.0449, 0.6597, 0.5347, 0.8402],\n",
" [0.9294, 0.9639, 0.6312, 0.1752, 0.7721],\n", " [0.0048, 0.9231, 0.0311, 0.2545, 0.0409],\n",
" [0.5533, 0.3656, 0.9329, 0.8796, 0.9513],\n", " [0.6506, 0.8651, 0.7558, 0.1086, 0.8135],\n",
" [0.4949, 0.0972, 0.2892, 0.7570, 0.2847]], device='cuda:0')\n", " [0.1083, 0.0039, 0.6049, 0.3596, 0.1359]], device='cuda:0')\n",
"tensor([[0.0962, 0.3125, 0.7327, 0.5982, 0.4624],\n", "tensor([[0.2854, 0.3384, 0.6473, 0.0433, 0.5640],\n",
" [0.4655, 0.4890, 0.9603, 0.4339, 0.0524],\n", " [0.3960, 0.0449, 0.6597, 0.5347, 0.8402],\n",
" [0.9294, 0.9639, 0.6312, 0.1752, 0.7721],\n", " [0.0048, 0.9231, 0.0311, 0.2545, 0.0409],\n",
" [0.5533, 0.3656, 0.9329, 0.8796, 0.9513],\n", " [0.6506, 0.8651, 0.7558, 0.1086, 0.8135],\n",
" [0.4949, 0.0972, 0.2892, 0.7570, 0.2847]], dtype=torch.float64)\n" " [0.1083, 0.0039, 0.6049, 0.3596, 0.1359]], dtype=torch.float64)\n"
] ]
} }
], ],
@ -295,12 +282,13 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"11.4 ms ± 60.2 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" "11.4 ms ± 28.8 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
] ]
} }
], ],
"source": [ "source": [
"%%timeit\n", "%%timeit\n",
"# Calculate the projection matrix of x on the GPU\n",
"H = x.mm( (x.t().mm(x)).inverse() ).mm(x.t())" "H = x.mm( (x.t().mm(x)).inverse() ).mm(x.t())"
] ]
}, },
@ -341,11 +329,11 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"tensor([[0.4303, 0.7364, 0.1235, 0.7786, 0.7036],\n", "tensor([[0.1101, 0.7887, 0.0641, 0.1327, 0.1681],\n",
" [0.3256, 0.4515, 0.7994, 0.9814, 0.7705],\n", " [0.7914, 0.7248, 0.7731, 0.2662, 0.4908],\n",
" [0.2292, 0.5194, 0.4354, 0.3964, 0.5804],\n", " [0.2451, 0.3568, 0.4006, 0.2099, 0.5212],\n",
" [0.8855, 0.5156, 0.9321, 0.9555, 0.4150],\n", " [0.6195, 0.5120, 0.5212, 0.7321, 0.2272],\n",
" [0.0640, 0.0665, 0.1170, 0.9547, 0.2668]], device='cuda:0')\n" " [0.2374, 0.4540, 0.0868, 0.9393, 0.1561]], device='cuda:0')\n"
] ]
} }
], ],
@ -376,11 +364,11 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"tensor([[1.0966e-03, 3.5866e-04, 4.0044e-04, 3.2466e-04, 2.3044e-04],\n", "tensor([[ 6.4681e-04, -1.5392e-05, 3.3608e-04, 2.1025e-04, 8.0912e-05],\n",
" [3.5866e-04, 9.7424e-04, 2.8649e-04, 8.2904e-04, 2.0482e-04],\n", " [-1.5392e-05, 5.0718e-04, -1.1769e-04, -2.3084e-05, -2.3264e-04],\n",
" [4.0044e-04, 2.8649e-04, 5.4179e-04, 1.2729e-04, 9.4659e-05],\n", " [ 3.3608e-04, -1.1769e-04, 6.9678e-04, 2.2663e-04, -1.8900e-04],\n",
" [3.2466e-04, 8.2904e-04, 1.2729e-04, 1.3005e-03, 6.6951e-06],\n", " [ 2.1025e-04, -2.3084e-05, 2.2663e-04, 6.0036e-04, 2.7787e-04],\n",
" [2.3044e-04, 2.0482e-04, 9.4659e-05, 6.6950e-06, 1.3420e-03]],\n", " [ 8.0912e-05, -2.3264e-04, -1.8900e-04, 2.7787e-04, 1.4208e-03]],\n",
" device='cuda:0')\n" " device='cuda:0')\n"
] ]
} }
@ -399,11 +387,11 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"tensor([[1.0966e-03, 3.5866e-04, 4.0044e-04, 3.2466e-04, 2.3044e-04],\n", "tensor([[ 6.4681e-04, -1.5392e-05, 3.3608e-04, 2.1025e-04, 8.0912e-05],\n",
" [3.5866e-04, 9.7424e-04, 2.8649e-04, 8.2904e-04, 2.0482e-04],\n", " [-1.5392e-05, 5.0718e-04, -1.1769e-04, -2.3084e-05, -2.3264e-04],\n",
" [4.0044e-04, 2.8649e-04, 5.4179e-04, 1.2729e-04, 9.4659e-05],\n", " [ 3.3608e-04, -1.1769e-04, 6.9678e-04, 2.2663e-04, -1.8900e-04],\n",
" [3.2466e-04, 8.2904e-04, 1.2729e-04, 1.3005e-03, 6.6951e-06],\n", " [ 2.1025e-04, -2.3084e-05, 2.2663e-04, 6.0036e-04, 2.7787e-04],\n",
" [2.3044e-04, 2.0482e-04, 9.4659e-05, 6.6950e-06, 1.3420e-03]],\n", " [ 8.0912e-05, -2.3264e-04, -1.8900e-04, 2.7787e-04, 1.4208e-03]],\n",
" dtype=torch.float64)\n" " dtype=torch.float64)\n"
] ]
} }

47
generate-Dockerfile.sh
View File

@ -4,10 +4,14 @@ cd $(cd -P -- "$(dirname -- "$0")" && pwd -P)
# Set the path of the generated Dockerfile # Set the path of the generated Dockerfile
export DOCKERFILE=".build/Dockerfile" export DOCKERFILE=".build/Dockerfile"
export STACKS_DIR=".build/docker-stacks" export STACKS_DIR=".build/docker-stacks"
export HEAD_COMMIT="c1c32938438151c7e2a22b5aa338caba2ec01da2" # please test the build of the commit in https://github.com/jupyter/docker-stacks/commits/master in advance
export HEAD_COMMIT="04f7f60d34a674a2964d96a6cb97c57a7870a828"
while [[ "$#" -gt 0 ]]; do case $1 in while [[ "$#" -gt 0 ]]; do case $1 in
-c|--commit) HEAD_COMMIT="$2"; shift;; -c|--commit) HEAD_COMMIT="$2"; shift;;
--no-datascience-notebook) no_datascience_notebook=1;;
--no-useful-packages) no_useful_packages=1;;
-s|--slim) no_datascience_notebook=1 && no_useful_packages=1;;
*) echo "Unknown parameter passed: $1" && *) echo "Unknown parameter passed: $1" &&
echo "Usage: $0 -c [sha-commit] # set the head commit of the docker-stacks submodule echo "Usage: $0 -c [sha-commit] # set the head commit of the docker-stacks submodule
(https://github.com/jupyter/docker-stacks/commits/master). default: $HEAD_COMMIT."; exit 1;; (https://github.com/jupyter/docker-stacks/commits/master). default: $HEAD_COMMIT."; exit 1;;
@ -23,11 +27,12 @@ if [[ "$HEAD_COMMIT" == "latest" ]]; then
cd $STACKS_DIR && git pull && cd - cd $STACKS_DIR && git pull && cd -
else else
export GOT_HEAD="false" export GOT_HEAD="false"
cd $STACKS_DIR && git reset --hard "$HEAD_COMMIT" > /dev/null 2>&1 && cd - && export GOT_HEAD="true" cd $STACKS_DIR && git pull && git reset --hard "$HEAD_COMMIT" > /dev/null 2>&1 && cd - && export GOT_HEAD="true"
echo "$HEAD" echo "$HEAD"
if [[ "$GOT_HEAD" == "false" ]]; then if [[ "$GOT_HEAD" == "false" ]]; then
echo "Given sha-commit is invalid." echo "Error: The given sha-commit is invalid."
echo "Usage: $0 -c [sha-commit] # set the head commit of the docker-stacks submodule (https://github.com/jupyter/docker-stacks/commits/master)." echo "Usage: $0 -c [sha-commit] # set the head commit of the docker-stacks submodule (https://github.com/jupyter/docker-stacks/commits/master)."
echo "Exiting"
exit 2 exit 2
else else
echo "Set head to given commit." echo "Set head to given commit."
@ -66,13 +71,17 @@ echo "
" >> $DOCKERFILE " >> $DOCKERFILE
cat $STACKS_DIR/scipy-notebook/Dockerfile | grep -v BASE_CONTAINER >> $DOCKERFILE cat $STACKS_DIR/scipy-notebook/Dockerfile | grep -v BASE_CONTAINER >> $DOCKERFILE
echo " # install Julia and R if not excluded or spare mode is used
############################################################################ if [[ "$no_datascience_notebook" != 1 ]]; then
################ Dependency: jupyter/datascience-notebook ################## echo "
############################################################################ ############################################################################
" >> $DOCKERFILE ################ Dependency: jupyter/datascience-notebook ##################
cat $STACKS_DIR/datascience-notebook/Dockerfile | grep -v BASE_CONTAINER >> $DOCKERFILE ############################################################################
" >> $DOCKERFILE
cat $STACKS_DIR/datascience-notebook/Dockerfile | grep -v BASE_CONTAINER >> $DOCKERFILE
else
echo "Set 'no-datascience-notebook', not installing the datascience-notebook with Julia and R."
fi
# Note that the following step also installs the cudatoolkit, which is # Note that the following step also installs the cudatoolkit, which is
# essential to access the GPU. # essential to access the GPU.
@ -83,13 +92,17 @@ echo "
" >> $DOCKERFILE " >> $DOCKERFILE
cat src/Dockerfile.gpulibs >> $DOCKERFILE cat src/Dockerfile.gpulibs >> $DOCKERFILE
# install useful packages if not excluded or spare mode is used
echo " if [[ "$no_useful_packages" != 1 ]]; then
############################################################################ echo "
############################ Useful packages ############################### ############################################################################
############################################################################ ############################ Useful packages ###############################
" >> $DOCKERFILE ############################################################################
cat src/Dockerfile.usefulpackages >> $DOCKERFILE " >> $DOCKERFILE
cat src/Dockerfile.usefulpackages >> $DOCKERFILE
else
echo "Set 'no-useful-packages', not installing stuff within src/Dockerfile.usefulpackages."
fi
# Copy the demo notebooks and change permissions # Copy the demo notebooks and change permissions
cp -r extra/Getting_Started data cp -r extra/Getting_Started data

14
src/Dockerfile.gpulibs
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@ -1,11 +1,15 @@
LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>" LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
# Install Tensorflow, check compatibility here: https://www.tensorflow.org/install/gpu # Install Tensorflow, check compatibility here: https://www.tensorflow.org/install/gpu
RUN conda install --quiet --yes \ # installation via conda leads to errors in version 4.8.2
'tensorflow-gpu=2.1*' \ #RUN conda install --quiet --yes \
'keras-gpu' && \ # 'tensorflow-gpu=2.1*' \
fix-permissions $CONDA_DIR && \ # 'keras-gpu' && \
fix-permissions /home/$NB_USER # fix-permissions $CONDA_DIR && \
# fix-permissions /home/$NB_USER
RUN pip install --upgrade pip && \
pip install --no-cache-dir "tensorflow-gpu>=2.1.*" && \
pip install --no-cache-dir keras
# Install PyTorch with dependencies # Install PyTorch with dependencies
RUN conda install --quiet --yes \ RUN conda install --quiet --yes \

2
src/Dockerfile.header
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@ -2,4 +2,4 @@
# The version of cudatoolkit must match those of the base image, see Dockerfile.pytorch # The version of cudatoolkit must match those of the base image, see Dockerfile.pytorch
FROM nvidia/cuda:10.1-base-ubuntu18.04 FROM nvidia/cuda:10.1-base-ubuntu18.04
LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>" LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
# The maintainers of subsequent sections may vary # This is a concatenated Dockerfile, the maintainers of subsequent sections may vary.