FROM nvidia/cuda:8.0-cudnn6-devel-ubuntu16.04

RUN apt-get update && apt-get install -y \
        build-essential \
        curl \
        git \
        libfreetype6-dev \
        libpng12-dev \
        libzmq3-dev \
        pkg-config \
        python-dev \
        python-numpy \
        python-pip \
        software-properties-common \
        swig \
        zip \
        zlib1g-dev \
        libcurl3-dev \
        && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

RUN apt-get install python-pip python-dev build-essential

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

# Set up grpc

RUN pip install enum34 futures mock six && \
    pip install --pre 'protobuf>=3.0.0a3' && \
    pip install -i https://testpypi.python.org/simple --pre grpcio

# Set up Bazel.

# We need to add a custom PPA to pick up JDK8, since trusty doesn't
# have an openjdk8 backport.  openjdk-r is maintained by a reliable contributor:
# Matthias Klose (https://launchpad.net/~doko).  It will do until
# we either update the base image beyond 14.04 or openjdk-8 is
# finally backported to trusty; see e.g.
#   https://bugs.launchpad.net/trusty-backports/+bug/1368094
RUN add-apt-repository -y ppa:openjdk-r/ppa && \
    apt-get update && \
    apt-get install -y openjdk-8-jdk openjdk-8-jre-headless && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# 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" >>/root/.bazelrc
# Similarly, we need to workaround sandboxing issues:
#   https://github.com/bazelbuild/bazel/issues/418
RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone" \
    >>/root/.bazelrc
ENV BAZELRC /root/.bazelrc
# Install the most recent bazel release.
ENV BAZEL_VERSION 0.5.4
WORKDIR /
RUN mkdir /bazel && \
    cd /bazel && \
    curl -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
    curl -fSsL -o /bazel/LICENSE 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 TensorFlow Serving
RUN git clone --recurse-submodules https://github.com/tensorflow/serving && \
  cd serving && \
  git checkout

# Build TensorFlow with the 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_CUDA_COMPUTE_CAPABILITIES=3.0,3.5,5.2,6.0,6.1

# Fix paths so that CUDNN can be found
# See https://github.com/tensorflow/tensorflow/issues/8264
RUN ls -lah /usr/local/cuda/lib64/*
RUN mkdir /usr/lib/x86_64-linux-gnu/include/ && \
  ln -s /usr/lib/x86_64-linux-gnu/include/cudnn.h /usr/lib/x86_64-linux-gnu/include/cudnn.h && \
  ln -s /usr/include/cudnn.h /usr/local/cuda/include/cudnn.h && \
  ln -s /usr/lib/x86_64-linux-gnu/libcudnn.so /usr/local/cuda/lib64/libcudnn.so && \
  ln -s /usr/lib/x86_64-linux-gnu/libcudnn.so.6 /usr/local/cuda/lib64/libcudnn.so.6

# Build TensorFlow Serving and Install it in /usr/local/bin
WORKDIR /serving
RUN bazel build -c opt --config=cuda \
    --crosstool_top=@local_config_cuda//crosstool:toolchain \
    tensorflow_serving/model_servers:tensorflow_model_server && \
    cp bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server /usr/local/bin/ && \
    bazel clean --expunge

CMD ["/bin/bash"]