Dockerfile

FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04

RUN apt-get update && apt-get install -y --no-install-recommends \
         build-essential \
         cmake \
         git \
         curl \
         vim \
         ca-certificates \
         libjpeg-dev  &&\
     rm -rf /var/lib/apt/lists/*


RUN curl -o ~/miniconda.sh -O  https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh  && \
     chmod +x ~/miniconda.sh && \
     ~/miniconda.sh -b -p /opt/conda && \
     rm ~/miniconda.sh && \
     /opt/conda/bin/conda install numpy pyyaml scipy ipython mkl mkl-include && \
     /opt/conda/bin/conda install -c pytorch magma-cuda90 && \
     /opt/conda/bin/conda install -c rdkit rdkit nox cairo && \
     /opt/conda/bin/conda clean -ya
ENV PATH /opt/conda/bin:$PATH
# This must be done before pip so that requirements.txt is available
WORKDIR /opt/pytorch
COPY . .

RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1
RUN LD_LIBRARY_PATH=/usr/local/cuda/lib64/stubs/:$LD_LIBRARY_PATH

RUN pip install --upgrade pip

RUN TORCH_CUDA_ARCH_LIST="3.5 5.2 6.0 6.1 7.0+PTX" TORCH_NVCC_FLAGS="-Xfatbin -compress-all" \
    CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" \
    conda install pytorch torchvision -c pytorch

RUN pip install sklearn

WORKDIR /workspace
RUN chmod -R a+w /workspace