tensorflow/tools/docker/Dockerfile.devel-gpu

FROM nvidia/cuda:9.0-base-ubuntu16.04

LABEL maintainer="Craig Citro <craigcitro@google.com>"

RUN apt-get update && apt-get install -y --no-install-recommends \
        build-essential \
        cuda-command-line-tools-9-0 \
        cuda-cublas-dev-9-0 \
        cuda-cudart-dev-9-0 \
        cuda-cufft-dev-9-0 \
        cuda-curand-dev-9-0 \
        cuda-cusolver-dev-9-0 \
        cuda-cusparse-dev-9-0 \
        curl \
        git \
        libcudnn7=7.2.1.38-1+cuda9.0 \
        libcudnn7-dev=7.2.1.38-1+cuda9.0 \
        libnccl2=2.2.13-1+cuda9.0 \
        libnccl-dev=2.2.13-1+cuda9.0 \
        libcurl3-dev \
        libfreetype6-dev \
        libhdf5-serial-dev \
        libpng12-dev \
        libzmq3-dev \
        pkg-config \
        python-dev \
        rsync \
        software-properties-common \
        unzip \
        zip \
        zlib1g-dev \
        wget \
        && \
    rm -rf /var/lib/apt/lists/* && \
    find /usr/local/cuda-9.0/lib64/ -type f -name 'lib*_static.a' -not -name 'libcudart_static.a' -delete && \
    rm /usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a

RUN apt-get update && \
        apt-get install nvinfer-runtime-trt-repo-ubuntu1604-4.0.1-ga-cuda9.0 && \
        apt-get update && \
        apt-get install libnvinfer4=4.1.2-1+cuda9.0 && \
        apt-get install libnvinfer-dev=4.1.2-1+cuda9.0

# Link NCCL libray and header where the build script expects them.
RUN mkdir /usr/local/cuda-9.0/lib &&  \
    ln -s /usr/lib/x86_64-linux-gnu/libnccl.so.2 /usr/local/cuda/lib/libnccl.so.2 && \
    ln -s /usr/include/nccl.h /usr/local/cuda/include/nccl.h

RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py && \
    python get-pip.py && \
    rm get-pip.py

RUN pip --no-cache-dir install \
        Pillow \
        h5py \
        ipykernel \
        jupyter \
        keras_applications==1.0.5 \
        keras_preprocessing==1.0.3 \
        matplotlib \
        mock \
        numpy \
        scipy \
        sklearn \
        pandas \
        && \
    python -m ipykernel.kernelspec

# RUN ln -s -f /usr/bin/python3 /usr/bin/python#

# Set up our notebook config.
COPY jupyter_notebook_config.py /root/.jupyter/

# Jupyter has issues with being run directly:
#   https://github.com/ipython/ipython/issues/7062
# We just add a little wrapper script.
COPY run_jupyter.sh /

# Set up Bazel.

# Running bazel inside a `docker build` command causes trouble, cf:
#   https://github.com/bazelbuild/bazel/issues/134
# The easiest solution is to set up a bazelrc file forcing --batch.
RUN echo "startup --batch" >>/etc/bazel.bazelrc
# Similarly, we need to workaround sandboxing issues:
#   https://github.com/bazelbuild/bazel/issues/418
RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone" \
    >>/etc/bazel.bazelrc
# Install the most recent bazel release.
ENV BAZEL_VERSION 0.15.0
WORKDIR /
RUN mkdir /bazel && \
    cd /bazel && \
    curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
    curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -o /bazel/LICENSE.txt https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE && \
    chmod +x bazel-*.sh && \
    ./bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
    cd / && \
    rm -f /bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh

# Download and build TensorFlow.
WORKDIR /tensorflow
RUN git clone --branch=r1.11 --depth=1 https://github.com/tensorflow/tensorflow.git .

# Configure the build for our CUDA configuration.
ENV CI_BUILD_PYTHON python
ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
ENV TF_NEED_CUDA 1
ENV TF_NEED_TENSORRT 1
ENV TF_CUDA_COMPUTE_CAPABILITIES=3.5,5.2,6.0,6.1,7.0
ENV TF_CUDA_VERSION=9.0
ENV TF_CUDNN_VERSION=7

# NCCL 2.x
ENV TF_NCCL_VERSION=2

RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1 && \
    LD_LIBRARY_PATH=/usr/local/cuda/lib64/stubs:${LD_LIBRARY_PATH} \
    tensorflow/tools/ci_build/builds/configured GPU \
    bazel build -c opt --copt=-mavx --config=cuda \
	--cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" \
        tensorflow/tools/pip_package:build_pip_package && \
    rm /usr/local/cuda/lib64/stubs/libcuda.so.1 && \
    bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/pip && \
    pip --no-cache-dir install --upgrade /tmp/pip/tensorflow-*.whl && \
    rm -rf /tmp/pip && \
    rm -rf /root/.cache
# Clean up pip wheel and Bazel cache when done.

WORKDIR /root

# TensorBoard
EXPOSE 6006
# IPython
EXPOSE 8888