Dockerfile to compile TensorFlow Serving 1.5 using GPU

Dockerfile_TFserving_1_5

# docker build --pull -t $USER/tensorflow-serving-devel -f Dockerfile .
# export TF_SERVING_PORT=9000
# export TF_SERVING_MODEL_PATH=/tf_models/mymodel
# export CONTAINER_NAME=my_container
# CUDA_VISIBLE_DEVICES=0 docker run --runtime=nvidia -it -p $TF_SERVING_PORT:$TF_SERVING_PORT -v $TF_SERVING_MODEL_PATH:/root/tf_model --name $CONTAINER_NAME $USER/tensorflow-serving-devel  /root/serving/bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server --port=$TF_SERVING_PORT --enable_batching=true --model_base_path=/root/tf_model/
# docker start -ai $CONTAINER_NAME

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

ENV TF_CUDA_VERSION=9.0 \
	TF_CUDNN_VERSION=7 \
	TF_SERVING_COMMIT=tags/1.5.0 \
	BAZEL_VERSION=0.8.0

RUN apt-get update && apt-get install -y \
        build-essential \
        curl \
        git \
        libfreetype6-dev \
        libpng12-dev \
        libzmq3-dev \
        mlocate \
        pkg-config \
        python-dev \
        python-numpy \
        python-pip \
        software-properties-common \
        swig \
        zip \
        zlib1g-dev \
        libcurl3-dev \
        openjdk-8-jdk\
        openjdk-8-jre-headless \
        wget \
        && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# Set up grpc

RUN pip install mock grpcio

# Set up Bazel.

ENV BAZELRC /root/.bazelrc
# Install the most recent bazel release.
WORKDIR /root/
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.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

# compile TF serving with CUDA support

ENV TF_NEED_CUDA=1 \
	TF_NEED_S3=1 \
	TF_CUDA_COMPUTE_CAPABILITIES="3.5,5.2,6.1" \
	TF_NEED_GCP=1 \
	TF_NEED_JEMALLOC=0 \
	TF_NEED_HDFS=0 \
	TF_NEED_OPENCL=0 \
	TF_NEED_MKL=0 \
	TF_NEED_VERBS=0 \
	TF_NEED_MPI=0 \
	TF_NEED_GDR=0 \
	TF_ENABLE_XLA=0 \
	TF_CUDA_CLANG=0 \
	TF_NEED_OPENCL_SYCL=0 \
	CUDA_TOOLKIT_PATH=/usr/local/cuda \
	CUDNN_INSTALL_PATH=/usr/lib/x86_64-linux-gnu \
	GCC_HOST_COMPILER_PATH=/usr/bin/gcc \
	PYTHON_BIN_PATH=/usr/bin/python \
	CC_OPT_FLAGS="-march=native" \
	PYTHON_LIB_PATH=/usr/local/lib/python2.7/dist-packages

RUN cd /root && git clone --recurse-submodules https://github.com/tensorflow/serving

RUN cd /root/serving && \
	git checkout $TF_SERVING_COMMIT && \
	git submodule update --recursive --init

RUN cd /root/serving/tensorflow && \
	TF_SET_ANDROID_WORKSPACE= ./configure

RUN cd /root/serving && \
	bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.2 --config=cuda -k --verbose_failures  --crosstool_top=@local_config_cuda//crosstool:toolchain tensorflow_serving/model_servers:tensorflow_model_server

RUN ln -s /usr/local/cuda /usr/local/nvidia && \
	ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/libcuda.so.1

CMD ["/bin/bash"]