anchor.diff:  ENV CONDA_DIR='/opt/conda' \
       SHELL='/bin/bash' \
       NB_USER='geek' \
  -    NB_UID='1000'
  +    NB_UID='1000' \
  +    TF_VERSION='1.0.0'
  +
   ENV PATH=$CONDA_DIR/bin:$PATH \
       HOME=/home/$NB_USER
   
  
positive.code:     $CONDA_DIR/bin/conda install --quiet --yes conda==3.19.1 && \
      $CONDA_DIR/bin/conda config --system --add channels conda-forge && \
      conda clean -tipsy && \
      echo "jpeg 8*" >> /opt/conda/conda-meta/pinned && \ #https://github.com/jupyter/docker-stacks/issues/210
      conda install --quiet --yes \
      'notebook=4.2*' \
      && conda clean -tipsy
  
negative.code: WORKDIR /home/$NB_USER/work
  ENTRYPOINT ["tini", "--"]
  CMD ["start-notebook.sh"]
  COPY files/start-notebook.sh /usr/local/bin/
  COPY files/start-singleuser.sh /usr/local/bin/
  COPY files/jupyter_notebook_config.py /home/$NB_USER/.jupyter/
  RUN chown -R $NB_USER:users /home/$NB_USER/.jupyter && \
      chmod +x /usr/local/bin/*.sh
  
  # download tf 3.5 v1.0.0
  RUN pip3 install tensorflow==$TF_VERSION
  # RUN pip --no-cache-dir install \
  #     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp35-cp35m-linux_x86_64.whl
  
  # # install some sci packages
  # RUN pip --no-cache-dir install \
  #     pandas \
  #     scikit-learn \
  #     matplotlib \
  #     numpy \
  #     scipy && \
  #     apt-get clean && \
  #     rm -rf /var/lib/apt/lists/*
  
  EXPOSE 6006 8888