# ngraph-neon.cpu dockerfile used to build and test ngraph-neon on gpu platforms FROM nvidia/cuda:8.0-cudnn7-devel-ubuntu16.04 # try to get around issue with badsig #https://github.com/NVIDIA/nvidia-docker/issues/619 (with devel image) (based on this issue added this) RUN rm /etc/apt/sources.list.d/cuda.list # removing nvidia-ml.list file to avoid apt-get update error # "The method driver /usr/lib/apt/methods/https could not be found." RUN rm /etc/apt/sources.list.d/nvidia-ml.list RUN apt-get update && \ apt-get install -y sudo curl apt-transport-https && \ apt-get clean autoclean && \ apt-get autoremove -y RUN curl http://developer.download.nvidia.com/compute/cuda/repos/GPGKEY | sudo apt-key add - # install standard python 2 and 3 environment stuff RUN apt-get update && \ apt-get install -y python-dev python-pip software-properties-common && \ apt-get clean autoclean && \ apt-get autoremove -y RUN pip install --upgrade pip RUN pip install virtualenv pytest RUN apt-get update && \ apt-get install -y python3 python3-pip python3-dev python3-venv && \ apt-get clean autoclean && \ apt-get autoremove -y RUN pip3 install virtualenv pytest #install onnx dependencies to install ngraph RUN apt-get update && apt-get install -y protobuf-compiler libprotobuf-dev RUN apt-get update && apt-get install -y \ build-essential cmake \ clang-3.9 clang-format-3.9 \ git \ wget patch diffutils zlib1g-dev libtinfo-dev \ doxygen graphviz && \ apt-get clean autoclean && \ apt-get autoremove -y # create a symbolic link for gmake command RUN ln -s /usr/bin/make /usr/bin/gmake # need to use sphinx version 1.6 to build docs # installing with apt-get install python-sphinx installs sphinx version 1.3.6 only # added install for python-pip above and # installed sphinx with pip to get the updated version 1.6.5 # allows for make html build under the doc/source directory as an interim build process RUN pip install sphinx # breathe package required to build documentation RUN pip install breathe # need numpy to successfully build docs for python_api RUN pip install numpy # RUN python3 -m pip install m2r WORKDIR /home