build & push all image configurations (python-only mode)

.build/Dockerfile

@@ -303,6 +303,107 @@ 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 <[email protected]>"
+
+# 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
+
+# Julia installation
+# Default values can be overridden at build time
+# (ARGS are in lower case to distinguish them from ENV)
+# Check https://julialang.org/downloads/
+ARG julia_version="1.5.3"
+# SHA256 checksum
+ARG julia_checksum="f190c938dd6fed97021953240523c9db448ec0a6760b574afd4e9924ab5615f1"
+
+# R pre-requisites
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+    fonts-dejavu \
+    gfortran \
+    gcc && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Julia dependencies
+# install Julia packages in /opt/julia instead of $HOME
+ENV JULIA_DEPOT_PATH=/opt/julia \
+    JULIA_PKGDIR=/opt/julia \
+    JULIA_VERSION="${julia_version}"
+
+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 "${julia_checksum} *julia-${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 $NB_UID
+
+# R packages including IRKernel which gets installed globally.
+RUN conda install --quiet --yes \
+    'r-base=4.0.3'  \
+    'r-caret=6.0*' \
+    'r-crayon=1.3*' \
+    'r-devtools=2.3*' \
+    'r-forecast=8.13*' \ 
+    'r-hexbin=1.28*' \
+    'r-htmltools=0.5*' \
+    'r-htmlwidgets=1.5*' \ 
+    'r-irkernel=1.1*' \
+    'r-nycflights13=1.0*' \
+    'r-randomforest=4.6*' \
+    'r-rcurl=1.98*' \
+    'r-rmarkdown=2.6*' \
+    'r-rsqlite=2.2*' \
+    'r-shiny=1.5*' \
+    'r-tidyverse=1.3*' \
+    'rpy2=3.3*' && \
+    conda clean --all -f -y && \
+    fix-permissions "${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
 
 ############################################################################
@@ -314,7 +415,7 @@ LABEL maintainer="Christoph Schranz <[email protected]>"
 # Install Tensorflow, check compatibility here: https://www.tensorflow.org/install/gpu
 # installation via conda leads to errors in version 4.8.2
 RUN pip install --upgrade pip && \
-    pip install --no-cache-dir "tensorflow-gpu>=2.1.*" && \
+    pip install --no-cache-dir "tensorflow==2.3.2" && \
     pip install --no-cache-dir keras
 
 # Install PyTorch with dependencies
@@ -361,13 +462,13 @@ RUN jupyter labextension install jupyterlab-drawio
 RUN jupyter labextension install jupyter-leaflet
 RUN jupyter labextension install [email protected]
 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 pip install --no-cache-dir jupyter-tabnine==1.1.0  --user && \
+  jupyter nbextension install --py jupyter_tabnine --user && \
+  jupyter nbextension enable --py jupyter_tabnine --user && \
+  jupyter serverextension enable --py jupyter_tabnine --user
 RUN pip install --no-cache-dir jupyter_contrib_nbextensions \
- jupyter_nbextensions_configurator rise && \
-  jupyter nbextension enable codefolding/main
+  jupyter_nbextensions_configurator rise
+#  jupyter nbextension enable codefolding/main
 RUN jupyter labextension install @ijmbarr/jupyterlab_spellchecker
 
 RUN fix-permissions /home/$NB_USER

.gitignore

@@ -116,4 +116,6 @@ venv.bak/
 src/jupyter_notebook_config.json
 .idea
 /Deployment-notes.md
-/push_tag.sh
+/push_tag_full.sh
+/push_tag_python-only.sh
+/push_tag_slim.sh

README.md

@@ -65,7 +65,7 @@ The image of this repository is available on [Dockerhub](https://hub.docker.com/
    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 cschranz/gpu-jupyter:v1.2_cuda-10.1_ubuntu-18.04_python-only
    ```
    This starts an instance with of *GPU-Jupyter* the tag `v1.2_cuda-10.1_ubuntu-18.04_python-only` at [http://localhost:8848](http://localhost:8848) (port `8484`).
-   The default password is `asdf` which should be changed as described [below](#set-password). 
+   The default password is `gpu-jupyter` (previously `asdf`) which should be changed as described [below](#set-password). 
    Furthermore, data within the host's `data` directory is shared with the container.
    Other versions of GPU-Jupyter are available and listed on Dockerhub under  [Tags](https://hub.docker.com/r/cschranz/gpu-jupyter/tags?page=1&ordering=last_updated).
 
@@ -84,13 +84,13 @@ As soon as you have access to your GPU within Docker containers
 (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`.
+with the default password `gpu-jupyter` (previously `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  
+  ./generate-Dockerfile.sh --python-only
   docker build -t gpu-jupyter .build/  # will take a while
   docker run --gpus all -d -it -p 8848:8888 -v $(pwd)/data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes -e NB_UID="$(id -u)" -e NB_GID="$(id -g)" --user root --restart always --name gpu-jupyter_1 gpu-jupyter
   ``` 
@@ -147,7 +147,7 @@ Here the `docker-stack` `scipy-notebook` is used instead of `datascience-noteboo
 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` 
+* `--python-only|--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.
 
@@ -170,15 +170,16 @@ If an essential package is missing in the default stack, please let us know!
 
 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/). 
-The input with the default password `asdf` is appended by a arbitrary salt `e49e73b0eb0e` to `asdfe49e73b0eb0e` and should yield the hash string as shown in the config below.
+The input with the default password `gpu-jupyter` (previously `asdf`) is concatenated by an arbitrary salt `3b4b6378355` to `gpu-jupyter3b4b6378355` and is hashed to `642693b20f0a33bcad27b94293d0ed7db3408322`.
+
 **Never give away your own unhashed password!**
 
 Then update the config file as shown below and restart the service.
 
 ```json
 {
   "NotebookApp": {
-    "password": "sha1:e49e73b0eb0e:32edae7a5fd119045e699a0bd04f90819ca90cd6"
+    "password": "sha1:3b4b6378355:642693b20f0a33bcad27b94293d0ed7db3408322"
   }
 }
 ```
@@ -303,7 +304,7 @@ e.g., here it is **elk_datastack**.
 * **-r:** registry port is the port that is published by the registry service, default is `5000`.
 
 Now, *gpu-jupyter* will be accessible here on [localhost:8848](http://localhost:8848) 
-with the default password `asdf` and shares the network with the other data-source, i.e., 
+with the default password `gpu-jupyter` (previously `asdf`) and shares the network with the other data-source, i.e., 
 all ports of the data-source will be accessible within *GPU-Jupyter*, 
 even if they aren't routed it the source's `docker-compose` file.
 

build_push_all.sh

@@ -0,0 +1,54 @@
+#!/usr/bin/env bash
+cd $(cd -P -- "$(dirname -- "$0")" && pwd -P)
+
+export TAGNAME="v1.3_cuda-10.1_ubuntu-18.04"
+
+
+###################### build, run and push full image ##########################
+echo
+echo
+echo "build, run and push full image with tag $TAGNAME."
+bash generate-Dockerfile.sh
+docker build -t cschranz/gpu-jupyter:$TAGNAME .build/
+
+export IMG_ID=$(docker image ls | grep $TAGNAME | grep -v _python-only | grep -v _slim | head -1 | awk '{print $3}')
+echo "push image with ID $IMG_ID and Tag $TAGNAME ."
+
+docker tag $IMG_ID cschranz/gpu-jupyter:$TAGNAME
+docker rm -f gpu-jupyter_1
+docker run --gpus all -d -it -p 8848:8888 -v $(pwd)/data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes --user root --restart always --name gpu-jupyter_1 cschranz/gpu-jupyter:$TAGNAME
+
+docker push cschranz/gpu-jupyter:$TAGNAME &&
+docker save cschranz/gpu-jupyter:$TAGNAME | gzip > ../gpu-jupyter_tag-$TAGNAME.tar.gz
+
+
+###################### build and push slim image ##########################
+echo
+echo
+echo "build and push slim image with tag ${TAGNAME}_slim."
+bash generate-Dockerfile.sh --slim
+docker build -t cschranz/gpu-jupyter:${TAGNAME}_slim  .build/
+
+export IMG_ID=$(docker image ls | grep ${TAGNAME}_slim  | head -1 | awk '{print $3}')
+echo "push image with ID $IMG_ID and Tag ${TAGNAME}_slim."
+
+docker tag $IMG_ID cschranz/gpu-jupyter:${TAGNAME}_slim
+docker push cschranz/gpu-jupyter:${TAGNAME}_slim &&
+docker save cschranz/gpu-jupyter:${TAGNAME}_slim | gzip > ../gpu-jupyter_tag-${TAGNAME}_slim.tar.gz
+
+
+
+###################### build and push python-only image ##########################
+echo
+echo
+echo "build and push slim image with tag ${TAGNAME}_slim."
+bash generate-Dockerfile.sh --slim
+docker build -t cschranz/gpu-jupyter:${TAGNAME}_slim  .build/
+
+export IMG_ID=$(docker image ls | grep ${TAGNAME}_slim  | head -1 | awk '{print $3}')
+echo "push image with ID $IMG_ID and Tag ${TAGNAME}_slim."
+
+docker tag $IMG_ID cschranz/gpu-jupyter:${TAGNAME}_slim
+docker push cschranz/gpu-jupyter:${TAGNAME}_slim &&
+docker save cschranz/gpu-jupyter:${TAGNAME}_slim | gzip > ../gpu-jupyter_tag-${TAGNAME}_slim.tar.gz
+

generate-Dockerfile.sh

@@ -10,6 +10,7 @@ export HEAD_COMMIT="703d8b2dcb886be2fe5aa4660a48fbcef647e7aa"
 while [[ "$#" -gt 0 ]]; do case $1 in
   -c|--commit) HEAD_COMMIT="$2"; shift;;
   --no-datascience-notebook) no_datascience_notebook=1;;
+  --python-only) 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: $1" &&
@@ -87,7 +88,7 @@ if [[ "$no_datascience_notebook" != 1 ]]; then
   " >> $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."
+  echo "Set 'no-datascience-notebook' = 'python-only', not installing the datascience-notebook with Julia and R."
 fi
 
 # Note that the following step also installs the cudatoolkit, which is