anchor.diff:  RUN pip install virtualenv
   RUN pip install tensorflow==1.0.1
   
  -WORKDIR /root/ml4music-workshop/midi-rnn
  +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 /root/ml4music-workshop/tensorflow-wavenet
  +WORKDIR $DOCKER_HOME/ml4music-workshop/tensorflow-wavenet
   RUN virtualenv venv
  -COPY setup_wavenet_venv.sh /root/ml4music-workshop/tensorflow-wavenet/setup_wavenet_venv.sh
  -RUN /root/ml4music-workshop/tensorflow-wavenet/setup_wavenet_venv.sh
  +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 /root/ml4music-workshop
  +WORKDIR $DOCKER_HOME/ml4music-workshop
  +
  +RUN chown -R docker:docker ./
  +USER docker
   
   # expose tensorboard ports
   # 7006 - char-rnn
  
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: 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 $DOCKER_HOME
  RUN git clone https://github.com/brannondorsey/ml4music-workshop.git
  WORKDIR $DOCKER_HOME/ml4music-workshop
  RUN git submodule init
  RUN git submodule update
  
  