Dockerfile.devel-gpu

# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
FROM nvidia/cuda:10.0-base-ubuntu16.04 as base_build

ARG TF_SERVING_VERSION_GIT_BRANCH=master
ARG TF_SERVING_VERSION_GIT_COMMIT=head

LABEL maintainer=gvasudevan@google.com
LABEL tensorflow_serving_github_branchtag=${TF_SERVING_VERSION_GIT_BRANCH}
LABEL tensorflow_serving_github_commit=${TF_SERVING_VERSION_GIT_COMMIT}

ENV CUDNN_VERSION=7.4.1.5
ENV TF_TENSORRT_VERSION=5.0.2

RUN apt-get update && apt-get install -y --no-install-recommends \
        automake \
        build-essential \
        ca-certificates \
        cuda-command-line-tools-10-0 \
        cuda-cublas-dev-10-0 \
        cuda-cudart-dev-10-0 \
        cuda-cufft-dev-10-0 \
        cuda-curand-dev-10-0 \
        cuda-cusolver-dev-10-0 \
        cuda-cusparse-dev-10-0 \
        curl \
        git \
        libfreetype6-dev \
        libpng12-dev \
        libtool \
        libcudnn7=${CUDNN_VERSION}-1+cuda10.0 \
        libcudnn7-dev=${CUDNN_VERSION}-1+cuda10.0 \
        libcurl3-dev \
        libzmq3-dev \
        mlocate \
        openjdk-8-jdk\
        openjdk-8-jre-headless \
        pkg-config \
        python-dev \
        software-properties-common \
        swig \
        unzip \
        wget \
        zip \
        zlib1g-dev \
        && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/* && \
    find /usr/local/cuda-10.0/lib64/ -type f -name 'lib*_static.a' -not -name 'libcudart_static.a' -delete && \
    rm /usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a

# The 'apt-get install' of the nvinfer-runtime-trt-repo-* library adds a new
# list which contains libnvinfer library, so it needs another 'apt-get update'
# to retrieve that list before it can actually install the library.
RUN apt-get update && \
    apt-get install --no-install-recommends \
        nvinfer-runtime-trt-repo-ubuntu1604-${TF_TENSORRT_VERSION}-ga-cuda10.0 && \
    apt-get update && \
    apt-get install --no-install-recommends \
        libnvinfer5=${TF_TENSORRT_VERSION}-1+cuda10.0 \
        libnvinfer-dev=${TF_TENSORRT_VERSION}-1+cuda10.0 && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/* && \
    rm /usr/lib/x86_64-linux-gnu/libnvinfer_static.a && \
    rm /usr/lib/x86_64-linux-gnu/libnvinfer_plugin_static.a && \
    rm /usr/lib/x86_64-linux-gnu/libnvcaffe_parser* && \
    rm /usr/lib/x86_64-linux-gnu/libnvparsers*

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 \
    future>=0.17.1 \
    grpcio \
    h5py \
    keras_applications>=1.0.8 \
    keras_preprocessing>=1.1.0 \
    mock \
    numpy \
    requests

# Set up Bazel
ENV BAZEL_VERSION 0.24.1
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

# 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_NEED_TENSORRT 1
ENV TENSORRT_INSTALL_PATH=/usr/lib/x86_64-linux-gnu
ENV TF_CUDA_COMPUTE_CAPABILITIES=3.0,3.5,5.2,6.0,6.1,7.0
ENV TF_CUDA_VERSION=10.0
ENV TF_CUDNN_VERSION=7

# Fix paths so that CUDNN can be found: https://github.com/tensorflow/tensorflow/issues/8264
WORKDIR /
RUN mkdir /usr/lib/x86_64-linux-gnu/include/ && \
  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.${TF_CUDNN_VERSION} /usr/local/cuda/lib64/libcudnn.so.${TF_CUDNN_VERSION}

# For backward compatibility we need this line. After 1.13 we can safely remove
# it.
ENV TF_NCCL_VERSION=

# Set TMP for nvidia build environment
ENV TMP="/tmp"

# Download TF Serving sources (optionally at specific commit).
WORKDIR /tensorflow-serving
RUN git clone --branch=${TF_SERVING_VERSION_GIT_BRANCH} https://github.com/tensorflow/serving . && \
    git remote add upstream https://github.com/tensorflow/serving.git && \
    if [ "${TF_SERVING_VERSION_GIT_COMMIT}" != "head" ]; then git checkout ${TF_SERVING_VERSION_GIT_COMMIT} ; fi

FROM base_build as binary_build
# Build, and install TensorFlow Serving
ARG TF_SERVING_BUILD_OPTIONS="--config=nativeopt"
RUN echo "Building with build options: ${TF_SERVING_BUILD_OPTIONS}"
ARG TF_SERVING_BAZEL_OPTIONS=""
RUN echo "Building with Bazel options: ${TF_SERVING_BAZEL_OPTIONS}"

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} \
    bazel build --color=yes --curses=yes --config=cuda --copt="-fPIC"\
    ${TF_SERVING_BAZEL_OPTIONS} \
    --verbose_failures \
    --output_filter=DONT_MATCH_ANYTHING \
    ${TF_SERVING_BUILD_OPTIONS} \
    tensorflow_serving/model_servers:tensorflow_model_server && \
    cp bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server \
    /usr/local/bin/ && \
    rm /usr/local/cuda/lib64/stubs/libcuda.so.1

# Build and install TensorFlow Serving API
RUN bazel build --color=yes --curses=yes \
    ${TF_SERVING_BAZEL_OPTIONS} \
    --verbose_failures \
    --output_filter=DONT_MATCH_ANYTHING \
    ${TF_SERVING_BUILD_OPTIONS} \
    tensorflow_serving/tools/pip_package:build_pip_package && \
    bazel-bin/tensorflow_serving/tools/pip_package/build_pip_package \
    /tmp/pip && \
    pip --no-cache-dir install --upgrade \
    /tmp/pip/tensorflow_serving_api_gpu-*.whl && \
    rm -rf /tmp/pip

FROM binary_build as clean_build
# Clean up Bazel cache when done.
RUN bazel clean --expunge --color=yes && \
    rm -rf /root/.cache
CMD ["/bin/bash"]