#!/usr/bin/env bash set -e set -o pipefail # Find out the absolute path to where ./configure resides pushd `dirname $0` > /dev/null SOURCE_BASE_DIR=`pwd -P` popd > /dev/null PLATFORM="$(uname -s | tr 'A-Z' 'a-z')" function is_linux() { if [[ "${PLATFORM}" == "linux" ]]; then true else false fi } function is_macos() { if [[ "${PLATFORM}" == "darwin" ]]; then true else false fi } function is_windows() { # On windows, the shell script is actually running in msys if [[ "${PLATFORM}" =~ msys_nt*|mingw*|cygwin*|uwin* ]]; then true else false fi } function bazel_clean_and_fetch() { # bazel clean --expunge currently doesn't work on Windows # TODO(pcloudy): Re-enable it after bazel clean --expunge is fixed. if ! is_windows; then bazel clean --expunge fi bazel fetch "//tensorflow/... -//tensorflow/contrib/nccl/... \ -//tensorflow/examples/android/..." } # Delete any leftover BUILD files from the Makefile build, which would interfere # with Bazel parsing. MAKEFILE_DOWNLOAD_DIR=tensorflow/contrib/makefile/downloads if [ -d "${MAKEFILE_DOWNLOAD_DIR}" ]; then find ${MAKEFILE_DOWNLOAD_DIR} -type f -name '*BUILD' -delete fi ## Set up python-related environment settings while true; do fromuser="" if [ -z "$PYTHON_BIN_PATH" ]; then default_python_bin_path=$(which python || which python3 || true) read -p "Please specify the location of python. [Default is $default_python_bin_path]: " PYTHON_BIN_PATH fromuser="1" if [ -z "$PYTHON_BIN_PATH" ]; then PYTHON_BIN_PATH=$default_python_bin_path fi fi if [ -e "$PYTHON_BIN_PATH" ]; then break fi echo "Invalid python path. ${PYTHON_BIN_PATH} cannot be found" 1>&2 if [ -z "$fromuser" ]; then exit 1 fi PYTHON_BIN_PATH="" # Retry done ## Set up MKL related environment settings if false; then # Disable building with MKL for now while [ "$TF_NEED_MKL" == "" ]; do fromuser="" read -p "Do you wish to build TensorFlow with MKL support? [y/N] " INPUT fromuser="1" case $INPUT in [Yy]* ) echo "MKL support will be enabled for TensorFlow"; TF_NEED_MKL=1;; [Nn]* ) echo "No MKL support will be enabled for TensorFlow"; TF_NEED_MKL=0;; "" ) echo "No MKL support will be enabled for TensorFlow"; TF_NEED_MKL=0;; * ) echo "Invalid selection: " $INPUT;; esac done OSNAME=`uname -s` if [ "$TF_NEED_MKL" == "1" ]; then # TF_NEED_MKL DST=`dirname $0` ARCHIVE_BASENAME=mklml_lnx_2017.0.2.20170110.tgz GITHUB_RELEASE_TAG=v0.3 MKLURL="https://github.com/01org/mkl-dnn/releases/download/$GITHUB_RELEASE_TAG/$ARCHIVE_BASENAME" if ! [ -e "$DST/third_party/mkl/$ARCHIVE_BASENAME" ]; then wget --no-check-certificate -P $DST/third_party/mkl/ $MKLURL fi tar -xzf $DST/third_party/mkl/$ARCHIVE_BASENAME -C $DST/third_party/mkl/ extracted_dir_name="${ARCHIVE_BASENAME%.*}" MKL_INSTALL_PATH=$DST/third_party/mkl/$extracted_dir_name MKL_INSTALL_PATH=`${PYTHON_BIN_PATH} -c "import os; print(os.path.realpath(os.path.expanduser('${MKL_INSTALL_PATH}')))"` if [ "$OSNAME" == "Linux" ]; then # Full MKL configuration MKL_RT_LIB_PATH="lib/intel64/libmkl_rt.so" #${TF_MKL_EXT}#TODO version? MKL_RT_OMP_LIB_PATH="../compiler/lib/intel64/libiomp5.so" #TODO VERSION? # MKL-ML configuration MKL_ML_LIB_PATH="lib/libmklml_intel.so" #${TF_MKL_EXT}#TODO version? MKL_ML_OMP_LIB_PATH="lib/libiomp5.so" #TODO VERSION? elif [ "$OSNAME" == "Darwin" ]; then echo "Darwin is unsupported yet"; exit 1 fi if [ -e "$MKL_INSTALL_PATH/${MKL_ML_LIB_PATH}" ]; then ln -sf $MKL_INSTALL_PATH/${MKL_ML_LIB_PATH} third_party/mkl/ ln -sf $MKL_INSTALL_PATH/${MKL_ML_OMP_LIB_PATH} third_party/mkl/ ln -sf $MKL_INSTALL_PATH/include third_party/mkl/ ln -sf $MKL_INSTALL_PATH/include third_party/eigen3/mkl_include else echo "ERROR: $MKL_INSTALL_PATH/${MKL_ML_LIB_PATH} does not exist"; exit 1 fi if [ -z "$fromuser" ]; then exit 1 fi cat > third_party/mkl/mkl.config <> tools/bazel.rc for opt in $CC_OPT_FLAGS; do echo "build:opt --cxxopt=$opt --copt=$opt" >> tools/bazel.rc done # Run the gen_git_source to create links where bazel can track dependencies for # git hash propagation GEN_GIT_SOURCE=tensorflow/tools/git/gen_git_source.py chmod a+x ${GEN_GIT_SOURCE} "${PYTHON_BIN_PATH}" ${GEN_GIT_SOURCE} --configure "${SOURCE_BASE_DIR}" ## Set up SYCL-related environment settings while [ "$TF_NEED_OPENCL" == "" ]; do read -p "Do you wish to build TensorFlow with OpenCL support? [y/N] " INPUT case $INPUT in [Yy]* ) echo "OpenCL support will be enabled for TensorFlow"; TF_NEED_OPENCL=1;; [Nn]* ) echo "No OpenCL support will be enabled for TensorFlow"; TF_NEED_OPENCL=0;; "" ) echo "No OpenCL support will be enabled for TensorFlow"; TF_NEED_OPENCL=0;; * ) echo "Invalid selection: " $INPUT;; esac done ## Set up Cuda-related environment settings while [ "$TF_NEED_CUDA" == "" ]; do read -p "Do you wish to build TensorFlow with CUDA support? [y/N] " INPUT case $INPUT in [Yy]* ) echo "CUDA support will be enabled for TensorFlow"; TF_NEED_CUDA=1;; [Nn]* ) echo "No CUDA support will be enabled for TensorFlow"; TF_NEED_CUDA=0;; "" ) echo "No CUDA support will be enabled for TensorFlow"; TF_NEED_CUDA=0;; * ) echo "Invalid selection: " $INPUT;; esac done export TF_NEED_CUDA export TF_NEED_OPENCL if [[ "$TF_NEED_CUDA" == "0" ]] && [[ "$TF_NEED_OPENCL" == "0" ]]; then echo "Configuration finished" bazel_clean_and_fetch exit fi if [ "$TF_NEED_CUDA" == "1" ]; then # Set up which gcc nvcc should use as the host compiler # No need to set this on Windows while ! is_windows && true; do fromuser="" if [ -z "$GCC_HOST_COMPILER_PATH" ]; then default_gcc_host_compiler_path=$(which gcc || true) read -p "Please specify which gcc should be used by nvcc as the host compiler. [Default is $default_gcc_host_compiler_path]: " GCC_HOST_COMPILER_PATH fromuser="1" if [ -z "$GCC_HOST_COMPILER_PATH" ]; then GCC_HOST_COMPILER_PATH="$default_gcc_host_compiler_path" fi fi if [ -e "$GCC_HOST_COMPILER_PATH" ]; then export GCC_HOST_COMPILER_PATH break fi echo "Invalid gcc path. ${GCC_HOST_COMPILER_PATH} cannot be found" 1>&2 if [ -z "$fromuser" ]; then exit 1 fi GCC_HOST_COMPILER_PATH="" # Retry done # Find out where the CUDA toolkit is installed while true; do # Configure the Cuda SDK version to use. if [ -z "$TF_CUDA_VERSION" ]; then read -p "Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: " TF_CUDA_VERSION fi fromuser="" if [ -z "$CUDA_TOOLKIT_PATH" ]; then default_cuda_path=/usr/local/cuda if is_windows; then if [ -z "$CUDA_PATH" ]; then default_cuda_path="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v8.0" else default_cuda_path="$(cygpath -m "$CUDA_PATH")" fi fi read -p "Please specify the location where CUDA $TF_CUDA_VERSION toolkit is installed. Refer to README.md for more details. [Default is $default_cuda_path]: " CUDA_TOOLKIT_PATH fromuser="1" if [ -z "$CUDA_TOOLKIT_PATH" ]; then CUDA_TOOLKIT_PATH="$default_cuda_path" fi fi if [[ -z "$TF_CUDA_VERSION" ]]; then TF_CUDA_EXT="" else TF_CUDA_EXT=".$TF_CUDA_VERSION" fi if is_windows; then CUDA_RT_LIB_PATH="lib/x64/cudart.lib" elif is_linux; then CUDA_RT_LIB_PATH="lib64/libcudart.so${TF_CUDA_EXT}" elif is_macos; then CUDA_RT_LIB_PATH="lib/libcudart${TF_CUDA_EXT}.dylib" fi if [ -e "${CUDA_TOOLKIT_PATH}/${CUDA_RT_LIB_PATH}" ]; then export CUDA_TOOLKIT_PATH export TF_CUDA_VERSION break fi echo "Invalid path to CUDA $TF_CUDA_VERSION toolkit. ${CUDA_TOOLKIT_PATH}/${CUDA_RT_LIB_PATH} cannot be found" if [ -z "$fromuser" ]; then exit 1 fi # Retry TF_CUDA_VERSION="" CUDA_TOOLKIT_PATH="" done # Find out where the cuDNN library is installed while true; do # Configure the Cudnn version to use. if [ -z "$TF_CUDNN_VERSION" ]; then read -p "Please specify the Cudnn version you want to use. [Leave empty to use system default]: " TF_CUDNN_VERSION fi fromuser="" if [ -z "$CUDNN_INSTALL_PATH" ]; then default_cudnn_path=${CUDA_TOOLKIT_PATH} read -p "Please specify the location where cuDNN $TF_CUDNN_VERSION library is installed. Refer to README.md for more details. [Default is $default_cudnn_path]: " CUDNN_INSTALL_PATH fromuser="1" if [ -z "$CUDNN_INSTALL_PATH" ]; then CUDNN_INSTALL_PATH=$default_cudnn_path fi # Result returned from "read" will be used unexpanded. That make "~" unuseable. # Going through one more level of expansion to handle that. CUDNN_INSTALL_PATH=`"${PYTHON_BIN_PATH}" -c "import os; print(os.path.realpath(os.path.expanduser('${CUDNN_INSTALL_PATH}')))"` fi if [[ -z "$TF_CUDNN_VERSION" ]]; then TF_CUDNN_EXT="" else TF_CUDNN_EXT=".$TF_CUDNN_VERSION" fi if is_windows; then CUDA_DNN_LIB_PATH="lib/x64/cudnn.lib" CUDA_DNN_LIB_ALT_PATH="lib/x64/cudnn.lib" elif is_linux; then CUDA_DNN_LIB_PATH="lib64/libcudnn.so${TF_CUDNN_EXT}" CUDA_DNN_LIB_ALT_PATH="libcudnn.so${TF_CUDNN_EXT}" elif is_macos; then CUDA_DNN_LIB_PATH="lib/libcudnn${TF_CUDNN_EXT}.dylib" CUDA_DNN_LIB_ALT_PATH="libcudnn${TF_CUDNN_EXT}.dylib" fi if [ -e "$CUDNN_INSTALL_PATH/${CUDA_DNN_LIB_ALT_PATH}" -o -e "$CUDNN_INSTALL_PATH/${CUDA_DNN_LIB_PATH}" ]; then export TF_CUDNN_VERSION export CUDNN_INSTALL_PATH break fi if is_linux; then if ! type ldconfig > /dev/null 2>&1; then LDCONFIG_BIN=/sbin/ldconfig else LDCONFIG_BIN=ldconfig fi CUDNN_PATH_FROM_LDCONFIG="$($LDCONFIG_BIN -p | sed -n 's/.*libcudnn.so .* => \(.*\)/\1/p')" if [ -e "${CUDNN_PATH_FROM_LDCONFIG}${TF_CUDNN_EXT}" ]; then export TF_CUDNN_VERSION export CUDNN_INSTALL_PATH="$(dirname ${CUDNN_PATH_FROM_LDCONFIG})" break fi fi echo "Invalid path to cuDNN ${CUDNN_VERSION} toolkit. Neither of the following two files can be found:" echo "${CUDNN_INSTALL_PATH}/${CUDA_DNN_LIB_PATH}" echo "${CUDNN_INSTALL_PATH}/${CUDA_DNN_LIB_ALT_PATH}" if is_linux; then echo "${CUDNN_PATH_FROM_LDCONFIG}${TF_CUDNN_EXT}" fi if [ -z "$fromuser" ]; then exit 1 fi # Retry TF_CUDNN_VERSION="" CUDNN_INSTALL_PATH="" done # Configure the compute capabilities that TensorFlow builds for. # Since Cuda toolkit is not backward-compatible, this is not guaranteed to work. while true; do fromuser="" default_cuda_compute_capabilities="3.5,5.2" if [ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then cat << EOF Please specify a list of comma-separated Cuda compute capabilities you want to build with. You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus. Please note that each additional compute capability significantly increases your build time and binary size. EOF read -p "[Default is: \"3.5,5.2\"]: " TF_CUDA_COMPUTE_CAPABILITIES fromuser=1 fi if [ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then TF_CUDA_COMPUTE_CAPABILITIES=$default_cuda_compute_capabilities fi # Check whether all capabilities from the input is valid COMPUTE_CAPABILITIES=${TF_CUDA_COMPUTE_CAPABILITIES//,/ } ALL_VALID=1 for CAPABILITY in $COMPUTE_CAPABILITIES; do if [[ ! "$CAPABILITY" =~ [0-9]+.[0-9]+ ]]; then echo "Invalid compute capability: " $CAPABILITY ALL_VALID=0 break fi done if [ "$ALL_VALID" == "0" ]; then if [ -z "$fromuser" ]; then exit 1 fi else export TF_CUDA_COMPUTE_CAPABILITIES break fi TF_CUDA_COMPUTE_CAPABILITIES="" done if is_windows; then # The following three variables are needed for MSVC toolchain configuration in Bazel export CUDA_PATH="$CUDA_TOOLKIT_PATH" export CUDA_COMPUTE_CAPABILITIES="$TF_CUDA_COMPUTE_CAPABILITIES" export NO_WHOLE_ARCHIVE_OPTION=1 # Set GCC_HOST_COMPILER_PATH to keep cuda_configure.bzl happy export GCC_HOST_COMPILER_PATH="/usr/bin/dummy_compiler" fi # end of if "$TF_NEED_CUDA" == "1" fi # OpenCL configuration if [ "$TF_NEED_OPENCL" == "1" ]; then # Determine which C++ compiler should be used as the host compiler while true; do fromuser="" if [ -z "$HOST_CXX_COMPILER" ]; then default_cxx_host_compiler=$(which clang++-3.6 || true) read -p "Please specify which C++ compiler should be used as the host C++ compiler. [Default is $default_cxx_host_compiler]: " HOST_CXX_COMPILER fromuser="1" if [ -z "$HOST_CXX_COMPILER" ]; then HOST_CXX_COMPILER=$default_cxx_host_compiler fi fi if [ -e "$HOST_CXX_COMPILER" ]; then export HOST_CXX_COMPILER break fi echo "Invalid C++ compiler path. ${HOST_CXX_COMPILER} cannot be found" 1>&2 if [ -z "$fromuser" ]; then exit 1 fi HOST_CXX_COMPILER="" # Retry done # Determine which C compiler should be used as the host compiler while true; do fromuser="" if [ -z "$HOST_C_COMPILER" ]; then default_c_host_compiler=$(which clang-3.6 || true) read -p "Please specify which C compiler should be used as the host C compiler. [Default is $default_c_host_compiler]: " HOST_C_COMPILER fromuser="1" if [ -z "$HOST_C_COMPILER" ]; then HOST_C_COMPILER=$default_c_host_compiler fi fi if [ -e "$HOST_C_COMPILER" ]; then export HOST_C_COMPILER break fi echo "Invalid C compiler path. ${HOST_C_COMPILER} cannot be found" 1>&2 if [ -z "$fromuser" ]; then exit 1 fi HOST_C_COMPILER="" # Retry done while true; do # Configure the OPENCL version to use. TF_OPENCL_VERSION="1.2" # Point to ComputeCpp root if [ -z "$COMPUTECPP_TOOLKIT_PATH" ]; then default_computecpp_toolkit_path=/usr/local/computecpp read -p "Please specify the location where ComputeCpp for SYCL $TF_OPENCL_VERSION is installed. [Default is $default_computecpp_toolkit_path]: " COMPUTECPP_TOOLKIT_PATH fromuser="1" if [ -z "$COMPUTECPP_TOOLKIT_PATH" ]; then COMPUTECPP_TOOLKIT_PATH=$default_computecpp_toolkit_path fi fi if is_linux; then SYCL_RT_LIB_PATH="lib/libComputeCpp.so" fi if [ -e "${COMPUTECPP_TOOLKIT_PATH}/${SYCL_RT_LIB_PATH}" ]; then export COMPUTECPP_TOOLKIT_PATH break fi echo "Invalid SYCL $TF_OPENCL_VERSION library path. ${COMPUTECPP_TOOLKIT_PATH}/${SYCL_RT_LIB_PATH} cannot be found" if [ -z "$fromuser" ]; then exit 1 fi # Retry TF_OPENCL_VERSION="" COMPUTECPP_TOOLKIT_PATH="" done # end of if "$TF_NEED_OPENCL" == "1" fi bazel_clean_and_fetch echo "Configuration finished"