anchor.diff:    chown -R $SSH_USER:$SSH_USER /.sshd/user_keys/$SSH_USER && chmod 700 /.sshd/user_keys/$SSH_USER
   VOLUME /ssh-key/$SSH_USER
   
  +# -----–––---------------------- Cuda Dependency --------------------
  +RUN echo "deb http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/nvidia-ml.list
  +RUN apt-get update && apt-get install -y --no-install-recommends --allow-downgrades \
  +        --allow-change-held-packages \
  +         libnccl2=2.0.5-3+cuda9.0 \
  +         libnccl-dev=2.0.5-3+cuda9.0 &&\
  +     rm -rf /var/lib/apt/lists/*
  +
   # -------------------- Conda environment --------------------
   RUN curl -o ~/miniconda.sh -O  https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh  && \
        sh ~/miniconda.sh -b -p /conda
  
positive.code: RUN git clone --recursive https://github.com/pytorch/pytorch && \
      cd pytorch && \
      git submodule update --init && \
      TORCH_CUDA_ARCH_LIST="3.5 3.7 5.2 6.0 6.1+PTX" TORCH_NVCC_FLAGS="-Xfatbin -compress-all" \
      CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" \
      pip install -v .
  
  
negative.code: FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04
  # TODO: reduce size and complexity of image.
  
  RUN apt-get update && apt-get install -y \
  