anchor.diff:  FROM nvidia/cuda:8.0-devel-ubuntu16.04
  +
  +# create a non-root user named "docker"
  +# we will use this when the user is logged in
  +RUN useradd -ms /bin/bash docker
  +USER root
  +ENV DOCKER_HOME /home/docker
   
   # install apt dependencies and clone the repo
   RUN apt-get update
   RUN apt-get install -y git python python-pip
  -WORKDIR /root
  +WORKDIR $DOCKER_HOME
   RUN git clone https://github.com/brannondorsey/ml4music-workshop.git
  -WORKDIR /root/ml4music-workshop
  +WORKDIR $DOCKER_HOME/ml4music-workshop
   RUN git submodule init
   RUN git submodule update
   
  
positive.code: # 7008 - wavene7
  
  EXPOSE 7006
  EXPOSE 7007 
  EXPOSE 7008
  
  CMD tensorboard --port 7006 --logdir /root/ml4music-workshop/char-rnn-tensorflow/logs &> /dev/null && \
      tensorboard --port 7007 --logdir /root/ml4music-workshop/midi-rnn/experiments &> /dev/null && \
      tensorboard --port 7008 --logdir /root/ml4music-workshop/tensorflow-wavenet/logdir &> /dev/null && bash
  
negative.code: RUN pip install virtualenv
  RUN pip install tensorflow==1.0.1
  
  WORKDIR $DOCKER_HOME/ml4music-workshop/midi-rnn
  RUN pip install -r requirements.txt
  
  # install and setup a virtual env for tensorflow-wavenet
  # as it requires a conflicting version of tensorflow from char-rnn-tensorflow
  WORKDIR $DOCKER_HOME/ml4music-workshop/tensorflow-wavenet
  RUN virtualenv venv
  COPY setup_wavenet_venv.sh $DOCKER_HOME/ml4music-workshop/tensorflow-wavenet/setup_wavenet_venv.sh
  RUN $DOCKER_HOME/ml4music-workshop/tensorflow-wavenet/setup_wavenet_venv.sh
  RUN rm setup_wavenet_venv.sh
  
  WORKDIR $DOCKER_HOME/ml4music-workshop
  
  RUN chown -R docker:docker ./
  USER docker
  
  # expose tensorboard ports
  # 7006 - char-rnn
  