Tensorflow-centos7-docker

build-tf.sh

#!/usr/bin/env bash
set -e
# shellcheck disable=SC2155

PYTHON_BIN=${1:-python}

wget -c https://bootstrap.pypa.io/get-pip.py
$PYTHON_BIN get-pip.py --user

export TF_CUDA_PATHS=/usr/local/cuda,/usr/
export TF_NEED_GCP="1"
export TF_NEED_JEMALLOC="1"
export TF_NEED_HDFS="1"
export TF_NEED_S3="0"
export TF_NEED_GDR="0"
export TF_ENABLE_XLA="1"
export TF_NEED_VERBS="0"
export TF_NEED_OPENCL="0"
export TF_NEED_MPI=0
# export TF_DOWNLOAD_CLANG=1

PYTHON_BIN_PATH=$(which "$PYTHON_BIN")
export PYTHON_BIN_PATH
export PYTHON_LIB_PATH="$($PYTHON_BIN_PATH -c 'import site; print(site.getsitepackages()[0])')"
export GCC_HOST_COMPILER_PATH=$(which gcc)
export CC_OPT_FLAGS="-march=x86-64"

if [ "$TF_ENV_TYPE" = "gpu" ]
then
 export TF_NEED_CUDA="1"
 export TF_CUDA_VERSION="10.0"
 export TF_CUDNN_VERSION="7"
 export TF_CUDA_CLANG="0"
 export TF_CUDA_COMPUTE_CAPABILITIES="5.2,3.5,3.7,7.0"
fi

if [ "$BUILD_WITH_MKL" = "1" ]
then
  CONFIG_MKL="--config=mkl"
else
  CONFIG_MKL=""
fi

$PYTHON_BIN -m pip install --upgrade pip wheel setuptools
$PYTHON_BIN -m pip --no-cache-dir install \
    grpcio \
    h5py \
    keras_applications \
    keras_preprocessing \
    mock \
    numpy \
    requests \
    future \
    enum34 \
    tensorflow-estimator

bazel clean
./configure

bazel build -c opt --copt=-msse4.2 --copt=-mavx \
      --copt=-O3 ${CONFIG_MKL} --linkopt -ldl \
      --copt=${CC_OPT_FLAGS} \
      //tensorflow/tools/pip_package:build_pip_package \
      //tensorflow/tools/lib_package:libtensorflow_jni \
      //tensorflow/tools/lib_package:libtensorflow \
      //tensorflow/tools/lib_package:libtensorflow_proto \

mkdir -p /tfbuild/dist/wheel
mkdir -p /tfbuild/dist/bazel-bin/tools

bazel build  //tensorflow/tools/pip_package:build_pip_package
bazel-bin/tensorflow/tools/pip_package/build_pip_package  /tfbuild/dist/wheel
cp -RL bazel-bin/tensorflow/libtensorflow*.so* /tfbuild/dist/bazel-bin/.
cp -RL bazel-bin/tensorflow/java /tfbuild/dist/bazel-bin/.
cp -RL bazel-bin/tensorflow/tools/lib_package /tfbuild/dist/bazel-bin/tools/.

Dockerfile

FROM centos:7

RUN yum makecache
RUN yum install -y centos-release-SCL which yum-utils centos-release-scl-rh epel-release
RUN yum install -y  python27  \
		python27-python-devel \
		python27-python-wheel \
                java-1.8.0-openjdk-devel \
		devtoolset-8-toolchain \
		devtoolset-6-toolchain \
		devtoolset-7-toolchain \
		wget \
                gcc-c++ \
                devtoolset-8-c* \
                devtoolset-7-c* \
                yum-utils \
                hdf5 \
                hdf5-devel

RUN yum-config-manager --enable centos-sclo-rh-testing
RUN yum makecache
RUN yum install -y rh-python36  \
                   rh-python36-python-devel \
                   rh-python36-python-wheel

RUN rpm -ivh $PYTHON_37_RPM_BASE/$PYTHON_37_RPM

RUN yum groupinstall -y 'Development Tools'

RUN mkdir -p /tfbuild

# Install CUDA libraries
ENV CUDA_VERSION_MAJOR 10
ENV CUDA_VERSION_MINOR 0
ENV CUDA_VERSION_BUILD 130
ENV CUDA_VERSION $CUDA_VERSION_MAJOR.$CUDA_VERSION_MINOR.$CUDA_VERSION_BUILD
ENV CUDA_RPM cuda-repo-rhel7-$CUDA_VERSION-1.x86_64.rpm
ENV CUDA_REMOTE https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/
ENV CUDA_MACHINE_LEARNING_RPEO https://developer.download.nvidia.cn/compute/machine-learning/repos/rhel7/x86_64/

RUN wget -c $CUDA_REMOTE/$CUDA_RPM
RUN rpm -vih $CUDA_RPM
RUN yum install -y cuda-libraries-dev-10-0 cuda-toolkit-10-0
RUN ln -s /usr/local/cuda-10.0/lib64/stubs/libcuda.so /usr/local/cuda-10.0/lib64/libcuda.so.1

RUN rpm -ivh $CUDA_MACHINE_LEARNING_RPEO/libcudnn7-7.6.1.34-1.cuda10.0.x86_64.rpm
RUN rpm -ivh $CUDA_MACHINE_LEARNING_RPEO/libnccl-2.4.7-1+cuda10.0.x86_64.rpm

RUN rpm -ivh $CUDA_MACHINE_LEARNING_RPEO/libcudnn7-devel-7.6.1.34-1.cuda10.0.x86_64.rpm
RUN rpm -ivh $CUDA_MACHINE_LEARNING_RPEO/libnccl-devel-2.4.7-1+cuda10.0.x86_64.rpm

ENV BAZEL_VERSION 0.24.1

RUN wget  https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
    chmod +x bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
    ./bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
    rm bazel-$BAZEL_VERSION-installer-linux-x86_64.sh

RUN yum -y remove git*
RUN yum -y install  https://centos7.iuscommunity.org/ius-release.rpm
RUN yum -y install  git2u-all

COPY tensorflow-source.zip /tfbuild
RUN cd /tfbuild && unzip tensorflow-source.zip

ARG IMAGE_TYPE=cpu
ENV TF_ENV_TYPE=$IMAGE_TYPE

ARG PY_VER=27
ENV BUILD_PY_VER=$PY_VER

ARG USE_MKL=1
ENV BUILD_WITH_MKL=$USE_MKL

COPY entrypoint.sh /tfbuild/tensorflow-source
COPY build-tf.sh /tfbuild/tensorflow-source

WORKDIR /tfbuild/tensorflow-source/
CMD /tfbuild/tensorflow-source/entrypoint.sh $BUILD_PY_VER

entrypoint.sh

#!/usr/bin/env bash
set -e
# shellcheck disable=SC2155

if [ "$TF_ENV_TYPE" = "gpu" ]
then
    DEVTOOLSET="devtoolset-6"
else
    DEVTOOLSET="devtoolset-7"
fi

case $1 in
    27)
        # scl enable python2.7 and useit for build
        SCL_PYTHON=python27
        PYTHON_BUILD_VER=python2.7
        ;;
    36)
        # scl enable python3.6 and useit for build
        SCL_PYTHON=rh-python36
        PYTHON_BUILD_VER=python3.6
        ;;
    37)
        # scl enable python3.6, but use 3.7 for build
        SCL_PYTHON=rh-python36
        PYTHON_BUILD_VER=python3.7
        ;;
    *)
        echo "python version not specified"
        exit 1
        ;;
esac

scl enable $SCL_PYTHON $DEVTOOLSET \
    "/usr/bin/env bash -c '/tfbuild/tensorflow-source/build-tf.sh $PYTHON_BUILD_VER'"

Makefile

IMAGE_VERSION=1.15.2
IMAGE_TYPE?=cpu
IMAGE_NAME="tensorflow-$(IMAGE_TYPE):$(IMAGE_VERSION)"
PY_VER?=27
USE_MKL?=1

build: clean-dist create-dist build-image run-container

clean-dist:
	@sudo rm -rf $(PWD)/dist/*

create-dist:
	@mkdir -p $(PWD)/dist

build-image: tensorflow-source.zip
	docker build -t $(IMAGE_NAME) . \
	--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
	--build-arg PY_VER=$(PY_VER) \
	--build-arg USE_MKL=$(USE_MKL)

tensorflow-source.zip:
	git clone https://github.com/tensorflow/tensorflow -b v$(IMAGE_VERSION) tensorflow-source
	@zip -r tensorflow-source.zip tensorflow-source
	@rm -rf tensorflow-source

run-container:
	@docker run -v $(PWD)/dist:/tfbuild/dist $(IMAGE_NAME)

clean:
	rm -f tensorflow-source.zip