update docker-stacks, torchviz, dockerhub-image description

2021-01-05 12:39:30 +01:00
parent 49d0c6f49d
commit c250aea2fe
8 changed files with 183 additions and 225 deletions
--- a/.build/Dockerfile
+++ b/.build/Dockerfile
@@ -2,7 +2,7 @@

 # **Please do not change this file directly!**
 # To adapt this Dockerfile, adapt 'generate-Dockerfile.sh' or 'src/Dockerfile.usefulpackages'.
-# More information can be found in the documentation.
+# More information can be found in the README under configuration.


 # Use NVIDIA CUDA as base image and run the same installation as in the other packages.
@@ -22,7 +22,8 @@ RUN chmod 1777 /tmp && chmod 1777 /var/tmp
 # Ubuntu 20.04 (focal)
 # https://hub.docker.com/_/ubuntu/?tab=tags&name=focal
 # OS/ARCH: linux/amd64
-ARG ROOT_CONTAINER=ubuntu:focal-20200423@sha256:238e696992ba9913d24cfc3727034985abd136e08ee3067982401acdc30cbf3f
+ARG ROOT_CONTAINER=ubuntu:focal-20201106@sha256:4e4bc990609ed865e07afc8427c30ffdddca5153fd4e82c20d8f0783a291e241
+

 LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
 ARG NB_USER="jovyan"
@@ -34,13 +35,33 @@ SHELL ["/bin/bash", "-o", "pipefail", "-c"]

 USER root

+# ---- Miniforge installer ----
+# Default values can be overridden at build time
+# (ARGS are in lower case to distinguish them from ENV)
+# Check https://github.com/conda-forge/miniforge/releases
+# Conda version
+ARG conda_version="4.9.2"
+# Miniforge installer patch version
+ARG miniforge_patch_number="0"
+# Miniforge installer architecture
+ARG miniforge_arch="x86_64"
+# Python implementation to use 
+# can be either Miniforge3 to use Python or Miniforge-pypy3 to use PyPy
+ARG miniforge_python="Miniforge3"
+
+# Miniforge archive to install
+ARG miniforge_version="${conda_version}-${miniforge_patch_number}"
+# Miniforge installer
+ARG miniforge_installer="${miniforge_python}-${miniforge_version}-Linux-${miniforge_arch}.sh"
+# Miniforge checksum
+ARG miniforge_checksum="6321775eb2c02d7f51d3a9004ce0be839099f126f4099c781531428536669560"
+
 # Install all OS dependencies for notebook server that starts but lacks all
 # features (e.g., download as all possible file formats)
 ENV DEBIAN_FRONTEND noninteractive
 RUN apt-get update \
 && apt-get install -yq --no-install-recommends \
    wget \
-    bzip2 \
    ca-certificates \
    sudo \
    locales \
@@ -61,16 +82,21 @@ ENV CONDA_DIR=/opt/conda \
    LANG=en_US.UTF-8 \
    LANGUAGE=en_US.UTF-8
 ENV PATH=$CONDA_DIR/bin:$PATH \
-    HOME=/home/$NB_USER
+    HOME=/home/$NB_USER \
+    CONDA_VERSION="${conda_version}" \
+    MINIFORGE_VERSION="${miniforge_version}"

 # Copy a script that we will use to correct permissions after running certain commands
 COPY fix-permissions /usr/local/bin/fix-permissions
 RUN chmod a+rx /usr/local/bin/fix-permissions

 # Enable prompt color in the skeleton .bashrc before creating the default NB_USER
-RUN sed -i 's/^#force_color_prompt=yes/force_color_prompt=yes/' /etc/skel/.bashrc
+# hadolint ignore=SC2016
+RUN sed -i 's/^#force_color_prompt=yes/force_color_prompt=yes/' /etc/skel/.bashrc && \
+   # Add call to conda init script see https://stackoverflow.com/a/58081608/4413446
+   echo 'eval "$(command conda shell.bash hook 2> /dev/null)"' >> /etc/skel/.bashrc 

-# Create NB_USER wtih name jovyan user with UID=1000 and in the 'users' group
+# Create NB_USER with name jovyan user with UID=1000 and in the 'users' group
 # and make sure these dirs are writable by the `users` group.
 RUN echo "auth requisite pam_deny.so" >> /etc/pam.d/su && \
    sed -i.bak -e 's/^%admin/#%admin/' /etc/sudoers && \
@@ -83,42 +109,34 @@ RUN echo "auth requisite pam_deny.so" >> /etc/pam.d/su && \
    fix-permissions $CONDA_DIR

 USER $NB_UID
-WORKDIR $HOME
 ARG PYTHON_VERSION=default

 # Setup work directory for backward-compatibility
-RUN mkdir /home/$NB_USER/work && \
-    fix-permissions /home/$NB_USER
-
-# Install conda as jovyan and check the md5 sum provided on the download site
-ENV MINICONDA_VERSION=4.8.2 \
-    MINICONDA_MD5=87e77f097f6ebb5127c77662dfc3165e \
-    CONDA_VERSION=4.8.2
+RUN mkdir "/home/$NB_USER/work" && \
+    fix-permissions "/home/$NB_USER"

+# Install conda as jovyan and check the sha256 sum provided on the download site
 WORKDIR /tmp
-RUN wget --quiet https://repo.continuum.io/miniconda/Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh && \
-    echo "${MINICONDA_MD5} *Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh" | md5sum -c - && \
-    /bin/bash Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh -f -b -p $CONDA_DIR && \
-    rm Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh && \
+
+# Prerequisites installation: conda, pip, tini
+RUN wget --quiet "https://github.com/conda-forge/miniforge/releases/download/${miniforge_version}/${miniforge_installer}" && \
+    echo "${miniforge_checksum} *${miniforge_installer}" | sha256sum --check && \
+    /bin/bash "${miniforge_installer}" -f -b -p $CONDA_DIR && \
+    rm "${miniforge_installer}" && \
+    # Conda configuration see https://conda.io/projects/conda/en/latest/configuration.html
    echo "conda ${CONDA_VERSION}" >> $CONDA_DIR/conda-meta/pinned && \
-    conda config --system --prepend channels conda-forge && \
    conda config --system --set auto_update_conda false && \
    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 && \
    conda list python | grep '^python ' | tr -s ' ' | cut -d '.' -f 1,2 | sed 's/$/.*/' >> $CONDA_DIR/conda-meta/pinned && \
-    conda install --quiet --yes conda && \
-    conda install --quiet --yes pip && \
+    conda install --quiet --yes \
+    "conda=${CONDA_VERSION}" \
+    'pip' \
+    'tini=0.18.0' && \
    conda update --all --quiet --yes && \
-    conda clean --all -f -y && \
-    rm -rf /home/$NB_USER/.cache/yarn && \
-    fix-permissions $CONDA_DIR && \
-    fix-permissions /home/$NB_USER
-
-# Install Tini
-RUN conda install --quiet --yes 'tini=0.18.0' && \
    conda list tini | grep tini | tr -s ' ' | cut -d ' ' -f 1,2 >> $CONDA_DIR/conda-meta/pinned && \
    conda clean --all -f -y && \
+    rm -rf /home/$NB_USER/.cache/yarn && \
    fix-permissions $CONDA_DIR && \
    fix-permissions /home/$NB_USER

@@ -129,9 +147,9 @@ RUN conda install --quiet --yes 'tini=0.18.0' && \
 # Do all this in a single RUN command to avoid duplicating all of the
 # files across image layers when the permissions change
 RUN conda install --quiet --yes \
-    'notebook=6.0.3' \
-    'jupyterhub=1.1.0' \
-    'jupyterlab=2.1.3' && \
+    'notebook=6.1.6' \
+    'jupyterhub=1.3.0' \
+    'jupyterlab=2.2.9' && \
    conda clean --all -f -y && \
    npm cache clean --force && \
    jupyter notebook --generate-config && \
@@ -148,10 +166,16 @@ CMD ["start-notebook.sh"]

 # Copy local files as late as possible to avoid cache busting
 COPY start.sh start-notebook.sh start-singleuser.sh /usr/local/bin/
+# Currently need to have both jupyter_notebook_config and jupyter_server_config to support classic and lab
 COPY jupyter_notebook_config.py /etc/jupyter/

 # Fix permissions on /etc/jupyter as root
 USER root
+
+# Prepare upgrade to JupyterLab V3.0 #1205
+RUN sed -re "s/c.NotebookApp/c.ServerApp/g" \
+    /etc/jupyter/jupyter_notebook_config.py > /etc/jupyter/jupyter_server_config.py
+
 RUN fix-permissions /etc/jupyter/

 # Switch back to jovyan to avoid accidental container runs as root
@@ -173,29 +197,27 @@ USER root
 # Install all OS dependencies for fully functional notebook server
 RUN apt-get update && apt-get install -yq --no-install-recommends \
    build-essential \
-    emacs-nox \
    vim-tiny \
    git \
    inkscape \
-    jed \
    libsm6 \
    libxext-dev \
    libxrender1 \
    lmodern \
    netcat \
-    python-dev \
    # ---- nbconvert dependencies ----
    texlive-xetex \
    texlive-fonts-recommended \
    texlive-plain-generic \
-    # Optional dependency
-    texlive-fonts-extra \
    # ----
    tzdata \
    unzip \
-    nano \
+    nano-tiny \
    && apt-get clean && rm -rf /var/lib/apt/lists/*

+# Create alternative for nano -> nano-tiny
+RUN update-alternatives --install /usr/bin/nano nano /bin/nano-tiny 10
+
 # Switch back to jovyan to avoid accidental container runs as root
 USER $NB_UID

@@ -210,10 +232,10 @@ LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"

 USER root

-# ffmpeg for matplotlib anim & dvipng for latex labels
+# ffmpeg for matplotlib anim & dvipng+cm-super for latex labels
 RUN apt-get update && \
-    apt-get install -y --no-install-recommends ffmpeg dvipng && \
-    rm -rf /var/lib/apt/lists/*
+    apt-get install -y --no-install-recommends ffmpeg dvipng cm-super && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*

 USER $NB_UID

@@ -221,31 +243,29 @@ USER $NB_UID
 RUN conda install --quiet --yes \
    'beautifulsoup4=4.9.*' \
    'conda-forge::blas=*=openblas' \
-    'bokeh=2.0.*' \
+    'bokeh=2.2.*' \
    'bottleneck=1.3.*' \
-    'cloudpickle=1.4.*' \
+    'cloudpickle=1.6.*' \
    'cython=0.29.*' \
-    'dask=2.15.*' \
+    'dask=2020.12.*' \
    'dill=0.3.*' \
-    'h5py=2.10.*' \
-    'hdf5=1.10.*' \
-    'ipywidgets=7.5.*' \
+    'h5py=3.1.*' \
+    'ipywidgets=7.6.*' \
    'ipympl=0.5.*'\
-    'matplotlib-base=3.2.*' \
-    # numba update to 0.49 fails resolving deps.
-    'numba=0.48.*' \
+    'matplotlib-base=3.3.*' \
+    'numba=0.52.*' \
    'numexpr=2.7.*' \
-    'pandas=1.0.*' \
+    'pandas=1.1.*' \
    'patsy=0.5.*' \
-    'protobuf=3.11.*' \
+    'protobuf=3.14.*' \
    'pytables=3.6.*' \
-    'scikit-image=0.16.*' \
-    'scikit-learn=0.22.*' \
-    'scipy=1.4.*' \
-    'seaborn=0.10.*' \
+    'scikit-image=0.18.*' \
+    'scikit-learn=0.24.*' \
+    'scipy=1.5.*' \
+    'seaborn=0.11.*' \
    'sqlalchemy=1.3.*' \
-    'statsmodels=0.11.*' \
-    'sympy=1.5.*' \
+    'statsmodels=0.12.*' \
+    'sympy=1.7.*' \
    'vincent=0.4.*' \
    'widgetsnbextension=3.5.*'\
    'xlrd=1.2.*' \
@@ -283,102 +303,6 @@ RUN MPLBACKEND=Agg python -c "import matplotlib.pyplot" && \

 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
-
-# Fix DL4006
-SHELL ["/bin/bash", "-o", "pipefail", "-c"]
-
-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 $HOME
-ENV JULIA_DEPOT_PATH=/opt/julia
-ENV JULIA_PKGDIR=/opt/julia
-ENV JULIA_VERSION=1.4.1
-
-WORKDIR /tmp
-
-# hadolint ignore=SC2046
-RUN mkdir "/opt/julia-${JULIA_VERSION}" && \
-    wget -q https://julialang-s3.julialang.org/bin/linux/x64/$(echo "${JULIA_VERSION}" | cut -d. -f 1,2)"/julia-${JULIA_VERSION}-linux-x86_64.tar.gz" && \
-    echo "fd6d8cadaed678174c3caefb92207a3b0e8da9f926af6703fb4d1e4e4f50610a *julia-${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 $NB_UID
-
-# R packages including IRKernel which gets installed globally.
-RUN conda install --quiet --yes \
-    'r-base=3.6.3' \
-    'r-caret=6.0*' \
-    'r-crayon=1.3*' \
-    'r-devtools=2.3*' \
-    'r-forecast=8.12*' \
-    'r-hexbin=1.28*' \
-    'r-htmltools=0.4*' \
-    'r-htmlwidgets=1.5*' \
-    'r-irkernel=1.1*' \
-    'r-nycflights13=1.0*' \
-    'r-plyr=1.8*' \
-    'r-randomforest=4.6*' \
-    'r-rcurl=1.98*' \
-    'r-reshape2=1.4*' \
-    'r-rmarkdown=2.1*' \
-    'r-rsqlite=2.2*' \
-    'r-shiny=1.4*' \
-    'r-tidyverse=1.3*' \
-    'rpy2=3.1*' \
-    && \
-    conda clean --all -f -y && \
-    fix-permissions "${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"
-
 WORKDIR $HOME

 ############################################################################
@@ -403,6 +327,8 @@ RUN conda install --quiet --yes \
     torchvision \
     cudatoolkit=10.1 -c pytorch
 #    pip install torch_nightly -f https://download.pytorch.org/whl/nightly/cu90/torch_nightly.html && \
+RUN pip install  --no-cache-dir torchviz
+

 # Clean installation
 RUN conda clean --all -f -y && \
--- a/.build/docker-stacks
+++ b/.build/docker-stacks
--- a/.build/jupyter_notebook_config.py
+++ b/.build/jupyter_notebook_config.py
@@ -7,7 +7,7 @@ import os
 import errno
 import stat

-c = get_config()
+c = get_config()  # noqa: F821
 c.NotebookApp.ip = '0.0.0.0'
 c.NotebookApp.port = 8888
 c.NotebookApp.open_browser = False
--- a/.build/start.sh
+++ b/.build/start.sh
@@ -47,19 +47,6 @@ if [ $(id -u) == 0 ] ; then
        usermod -d /home/$NB_USER -l $NB_USER jovyan
    fi

-    # Handle case where provisioned storage does not have the correct permissions by default
-    # Ex: default NFS/EFS (no auto-uid/gid)
-    if [[ "$CHOWN_HOME" == "1" || "$CHOWN_HOME" == 'yes' ]]; then
-        echo "Changing ownership of /home/$NB_USER to $NB_UID:$NB_GID with options '${CHOWN_HOME_OPTS}'"
-        chown $CHOWN_HOME_OPTS $NB_UID:$NB_GID /home/$NB_USER
-    fi
-    if [ ! -z "$CHOWN_EXTRA" ]; then
-        for extra_dir in $(echo $CHOWN_EXTRA | tr ',' ' '); do
-            echo "Changing ownership of ${extra_dir} to $NB_UID:$NB_GID with options '${CHOWN_EXTRA_OPTS}'"
-            chown $CHOWN_EXTRA_OPTS $NB_UID:$NB_GID $extra_dir
-        done
-    fi
-
    # handle home and working directory if the username changed
    if [[ "$NB_USER" != "jovyan" ]]; then
        # changing username, make sure homedir exists
@@ -76,11 +63,24 @@ if [ $(id -u) == 0 ] ; then
        fi
    fi

+    # Handle case where provisioned storage does not have the correct permissions by default
+    # Ex: default NFS/EFS (no auto-uid/gid)
+    if [[ "$CHOWN_HOME" == "1" || "$CHOWN_HOME" == 'yes' ]]; then
+        echo "Changing ownership of /home/$NB_USER to $NB_UID:$NB_GID with options '${CHOWN_HOME_OPTS}'"
+        chown $CHOWN_HOME_OPTS $NB_UID:$NB_GID /home/$NB_USER
+    fi
+    if [ ! -z "$CHOWN_EXTRA" ]; then
+        for extra_dir in $(echo $CHOWN_EXTRA | tr ',' ' '); do
+            echo "Changing ownership of ${extra_dir} to $NB_UID:$NB_GID with options '${CHOWN_EXTRA_OPTS}'"
+            chown $CHOWN_EXTRA_OPTS $NB_UID:$NB_GID $extra_dir
+        done
+    fi
+
    # Change UID:GID of NB_USER to NB_UID:NB_GID if it does not match
    if [ "$NB_UID" != $(id -u $NB_USER) ] || [ "$NB_GID" != $(id -g $NB_USER) ]; then
        echo "Set user $NB_USER UID:GID to: $NB_UID:$NB_GID"
        if [ "$NB_GID" != $(id -g $NB_USER) ]; then
-            groupadd -g $NB_GID -o ${NB_GROUP:-${NB_USER}}
+            groupadd -f -g $NB_GID -o ${NB_GROUP:-${NB_USER}}
        fi
        userdel $NB_USER
        useradd --home /home/$NB_USER -u $NB_UID -g $NB_GID -G 100 -l $NB_USER
@@ -101,7 +101,7 @@ if [ $(id -u) == 0 ] ; then
    echo "Executing the command: ${cmd[@]}"
    exec sudo -E -H -u $NB_USER PATH=$PATH XDG_CACHE_HOME=/home/$NB_USER/.cache PYTHONPATH=${PYTHONPATH:-} "${cmd[@]}"
 else
-    if [[ "$NB_UID" == "$(id -u jovyan)" && "$NB_GID" == "$(id -g jovyan)" ]]; then
+    if [[ "$NB_UID" == "$(id -u jovyan 2>/dev/null)" && "$NB_GID" == "$(id -g jovyan 2>/dev/null)" ]]; then
        # User is not attempting to override user/group via environment
        # variables, but they could still have overridden the uid/gid that
        # container runs as. Check that the user has an entry in the passwd
--- a/README.md
+++ b/README.md
@@ -21,62 +21,81 @@ The image of this repository is available on [Dockerhub](https://hub.docker.com/

 ## Requirements

-1.  A NVIDIA GPU
+1.  A computer with 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+**.
-3.  Get access to your GPU via CUDA drivers within Docker containers. Therfore, check out this 
-[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 
-    in [NVIDIA-docker](https://github.com/NVIDIA/nvidia-docker). 
+3.  Get access to your GPU via CUDA drivers within Docker containers.
    You can be sure that you can access your GPU within Docker, 
-    if the command `docker run --gpus all nvidia/cuda:10.1-base-ubuntu18.04 nvidia-smi`
+    if the command `docker run --gpus all nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04 nvidia-smi`
    returns a result similar to this one:
    ```bash
-    Mon Jun 22 09:06:28 2020       
+    Tue Jan  5 09:38:21 2021       
    +-----------------------------------------------------------------------------+
-    | NVIDIA-SMI 440.82       Driver Version: 440.82       CUDA Version: 10.1     |
+    | NVIDIA-SMI 450.80.02    Driver Version: 450.80.02    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. |
+    |                               |                      |               MIG M. |
    |===============================+======================+======================|
    |   0  GeForce RTX 207...  Off  | 00000000:01:00.0  On |                  N/A |
-    |  0%   46C    P8     9W / 215W |    424MiB /  7974MiB |      6%      Default |
+    |  0%   40C    P8     7W / 215W |    360MiB /  7974MiB |      1%      Default |
+    |                               |                      |                  N/A |
    +-------------------------------+----------------------+----------------------+
                                                                                   
    +-----------------------------------------------------------------------------+
-    | Processes:                                                       GPU Memory |
-    |  GPU       PID   Type   Process name                             Usage      |
+    | Processes:                                                                  |
+    |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
+    |        ID   ID                                                   Usage      |
    |=============================================================================|
    +-----------------------------------------------------------------------------+
    ``` 
-4. Clone the Repository or pull the image from 
-    [Dockerhub](https://hub.docker.com/repository/docker/cschranz/gpu-jupyter):
+    If you don't get an output similar than this one, follow the installation steps in this 
+[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 
+    installed within the Docker containers using [NVIDIA-docker](https://github.com/NVIDIA/nvidia-docker).
+    It is also important to keep your installed CUDA version in mind, when you pull images. 
+    **You can't run images based on `nvidia/cuda:11.1` if you have only CUDA version 10.1 installed.**
+    Check your host's CUDA-version with `nvcc --version` and update to at least 
+    the same version you want to pull.
+    
+4. Pull and run the image. This can last some hours, as a whole data-science 
+    environment will be downloaded:
   ```bash
-    git clone https://github.com/iot-salzburg/gpu-jupyter.git
-    cd gpu-jupyter
+   cd your-working-directory 
+   docker run --gpus all -d -it -p 8848:8888 -v data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes --user root cschranz/gpu-jupyter:v1.1_cuda-10.1_ubuntu-18.04_python-only
   ```
+   This starts a new instance of the GPU-Jupyter service on at [http://localhost:8848](http://localhost:8848) (port `8484`).
+   The default password is `asdf` which should be changed as described [below](#set-password). 
+   Furthermore, data within the host's `data` directory is shared with the container.
   
-## Quickstart
+Within the Jupyterlab instance, you can check if you can access your GPU by opening a new terminal window and running
+`nvidia-smi`. In terminal windows, you can also install new packages for your own projects. 
+Some example code can be found in the repository under `extra/Getting_Started`.
+If you want to learn more about Jupyterlab, check out this [tutorial](https://www.youtube.com/watch?v=7wfPqAyYADY). 

-First of all, it is necessary to generate the `Dockerfile` that is based on 
+
+## Build a modified version
+
+First, it is necessary to generate the `Dockerfile` in `.build`, that is based on 
 the NIVIDA base image and the [docker-stacks](https://github.com/jupyter/docker-stacks).
 As soon as you have access to your GPU within Docker containers 
-(make sure the command `docker run --gpus all nvidia/cuda:10.1-base-ubuntu18.04 nvidia-smi` 
+(make sure the command `docker run --gpus all nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04 nvidia-smi` 
 shows your GPU statistics), you can generate the Dockerfile, build and run it.
 The following commands will start *GPU-Jupyter* on [localhost:8848](http://localhost:8848) 
 with the default password `asdf`.

  ```bash
+  git clone https://github.com/iot-salzburg/gpu-jupyter.git
+  cd gpu-jupyter
  # generate a Dockerfile with python and without Julia and R
  ./generate-Dockerfile.sh --no-datascience-notebook  
  docker build -t gpu-jupyter .build/  # will take a while
-  docker run -d -p [port]:8888 gpu-jupyter  # starts gpu-jupyter WITHOUT GPU support
+  docker run --gpus all -d -it -p 8848:8888 -v $pwd/data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes --user root --restart always --name gpu-jupyter_1 gpu-jupyter 
  ``` 

-To run the container WITH GPU support, a local data volume and some other configurations, run:
-  ```bash
-docker run --gpus all -d -it -p 8848:8888 -v $(pwd)/data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes --user root --restart always --name gpu-jupyter_1 gpu-jupyter 
-``` 
+This starts a container WITH GPU support, a shared local data volume `data`  
+and some other configurations like root permissions which are necessary to install packages within the container.
+For more configurations, scroll down to [Configuration of the Dockerfile-Generation](#configuration-of-the-dockerfile-generation).

 ### Start via Docker Compose

@@ -92,14 +111,16 @@ underlying `docker-compose.yml`:
  
 With these commands we can see if everything worked well:
 ```bash
-bash show-local.sh  # a env-var safe wrapper for 'docker-compose logs -f'
 docker ps
-docker logs [service-name]
+docker logs [service-name]  # or
+bash show-local.sh  # a env-var safe wrapper for 'docker-compose logs -f'
 ```

 In order to stop the local deployment, run:

  ```bash
+docker ps
+docker rm -f [service-name]  # or
  ./stop-local.sh
  ```
 
@@ -134,13 +155,16 @@ the essential `gpulibs` are installed, but not the packages within `src/Dockerfi

 ### Custom Installations

-**As `.build/Dockerfile` is overwritten, it is suggested to append custom installations either
+Custom packages can be installed within a container, or by modifying the file
+`src/Dockerfile.usefulpackages`.
+**As `.build/Dockerfile` is overwritten each time a Dockerfile is generated, 
+it is suggested to append custom installations either
 within `src/Dockerfile.usefulpackages` or in `generate-Dockerfile.sh`.**
-If you think some package is missing in the default stack, please let us know!
+If an essential package is missing in the default stack, please let us know!



-### Set the Password
+### Set Password

 Please set a new password using `src/jupyter_notebook_config.json`.
 Therefore, hash your password in the form (password)(salt) using a sha1 hash generator, e.g., the sha1 generator of [sha1-online.com](http://www.sha1-online.com/). 
@@ -162,24 +186,30 @@ Then update the config file as shown below and restart the service.
 
 #### Update CUDA to another version

-Please check version compatibilities for [CUDA and Pytorch](https://pytorch.org/get-started/locally/)
- respectively [CUDA and Tensorflow](https://www.tensorflow.org/install/gpu) previously. 
-To update CUDA to another version, change in `Dockerfile.header`
+The host's CUDA-version must be equal or higher than that of the
+container itself (in `Dockerfile.header`). 
+Check the host's version with `nvcc --version` and the version compatibilities 
+for CUDA-dependent packages as [Pytorch](https://pytorch.org/get-started/locally/)
+ respectively [Tensorflow](https://www.tensorflow.org/install/gpu) previously.
+Then modify, if supported, the CUDA-version in `Dockerfile.header` to, e.g.:
 the line:

-    FROM nvidia/cuda:10.1-base-ubuntu18.04
+    FROM nvidia/cuda:11.1-base-ubuntu20.04
    
 and in the `Dockerfile.pytorch` the line:

-    cudatoolkit=10.1
+    cudatoolkit=11.1

-Then re-generate and re-run the image, as closer described above:
+Then re-generate, re-build and run the updated image, as closer described above:
+Note that a change in the first line of the Dockerfile will re-build the whole image.

 ```bash
 ./generate-Dockerfile.sh
-./start-local.sh -p 8848
+docker build -t gpu-jupyter .build/  # will take a while
+docker run --gpus all -d -it -p 8848:8888 -v $pwd/data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes --user root --restart always --name gpu-jupyter_1 gpu-jupyter 
 ```

+
 #### Update Docker-Stack

 The [docker-stacks](https://github.com/jupyter/docker-stacks) are used as  a
--- a/generate-Dockerfile.sh
+++ b/generate-Dockerfile.sh
@@ -5,7 +5,7 @@ cd $(cd -P -- "$(dirname -- "$0")" && pwd -P)
 export DOCKERFILE=".build/Dockerfile"
 export STACKS_DIR=".build/docker-stacks"
 # please test the build of the commit in https://github.com/jupyter/docker-stacks/commits/master in advance
-export HEAD_COMMIT="04f7f60d34a674a2964d96a6cb97c57a7870a828"
+export HEAD_COMMIT="703d8b2dcb886be2fe5aa4660a48fbcef647e7aa"

 while [[ "$#" -gt 0 ]]; do case $1 in
  -c|--commit) HEAD_COMMIT="$2"; shift;;
--- a/src/Dockerfile.gpulibs
+++ b/src/Dockerfile.gpulibs
@@ -16,6 +16,8 @@ RUN conda install --quiet --yes \
     torchvision \
     cudatoolkit=10.1 -c pytorch
 #    pip install torch_nightly -f https://download.pytorch.org/whl/nightly/cu90/torch_nightly.html && \
+RUN pip install  --no-cache-dir torchviz
+

 # Clean installation
 RUN conda clean --all -f -y && \