Dockerfile.caffe_gpu

# docker build -t bvlc_caffe_nccl2 -f Dockerfile.caffe_gpu .
FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04
LABEL maintainer caffe-maint@googlegroups.com

RUN apt-get update && apt-get install -y --no-install-recommends \
        build-essential \
        cmake \
        git \
        wget \
        libatlas-base-dev \
        libboost-all-dev \
        libgflags-dev \
        libgoogle-glog-dev \
        libhdf5-serial-dev \
        libleveldb-dev \
        liblmdb-dev \
        libopencv-dev \
        libprotobuf-dev \
        libsnappy-dev \
        protobuf-compiler \
        python-dev \
        python-numpy \
        python-pip \
        python-setuptools \
        python-scipy && \
    rm -rf /var/lib/apt/lists/*

ENV CAFFE_ROOT=/opt/caffe
WORKDIR $CAFFE_ROOT

# FIXME: use ARG instead of ENV once DockerHub supports this
# https://github.com/docker/hub-feedback/issues/460
ENV CLONE_TAG=1.0

ARG NCCLVERSION=2.1.4-1+cuda9.0
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 \
        libnccl2=$NCCLVERSION \
        libnccl-dev=$NCCLVERSION && \
    rm -rf /var/lib/apt/lists/*

RUN git clone -b ${CLONE_TAG} --depth 1 https://github.com/BVLC/caffe.git . && \
    pip install --upgrade pip && \
    cd python && for req in $(cat requirements.txt) pydot; do pip install $req; done && cd ..


COPY Cuda.cmake .
RUN cp Cuda.cmake cmake/ && mkdir build && cd build && \
    cmake -DUSE_CUDNN=1 -DUSE_NCCL=1 .. && \
    make -j"$(nproc)"

ENV PYCAFFE_ROOT $CAFFE_ROOT/python
ENV PYTHONPATH $PYCAFFE_ROOT:$PYTHONPATH
ENV PATH $CAFFE_ROOT/build/tools:$PYCAFFE_ROOT:$PATH
RUN echo "$CAFFE_ROOT/build/lib" >> /etc/ld.so.conf.d/caffe.conf && ldconfig

WORKDIR /workspace