246 lines
8.8 KiB
Bash
Executable File
246 lines
8.8 KiB
Bash
Executable File
#!/usr/bin/env bash
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DO_NOT_SUBMIT_WARNING="Unofficial setting. DO NOT SUBMIT!!!"
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## Set up python-related environment settings
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while true; do
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fromuser=""
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if [ -z "$PYTHON_BIN_PATH" ]; then
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default_python_bin_path=$(which python)
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read -p "Please specify the location of python. [Default is $default_python_bin_path]: " PYTHON_BIN_PATH
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fromuser="1"
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if [ -z "$PYTHON_BIN_PATH" ]; then
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PYTHON_BIN_PATH=$default_python_bin_path
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fi
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fi
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if [ -e "$PYTHON_BIN_PATH" ]; then
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break
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fi
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echo "Invalid python path. ${PYTHON_BIN_PATH} cannot be found" 1>&2
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if [ -z "$fromuser" ]; then
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exit 1
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fi
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PYTHON_BIN_PATH=""
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# Retry
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done
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## Find swig path
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if [ -z "$SWIG_PATH" ]; then
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SWIG_PATH=`type -p swig 2> /dev/null`
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fi
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if [[ ! -e "$SWIG_PATH" ]]; then
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echo "Can't find swig. Ensure swig is in \$PATH or set \$SWIG_PATH."
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exit 1
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fi
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echo "$SWIG_PATH" > tensorflow/tools/swig/swig_path
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# Invoke python_config and set up symlinks to python includes
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(./util/python/python_config.sh --setup "$PYTHON_BIN_PATH";) || exit -1
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## Set up Cuda-related environment settings
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while [ "$TF_NEED_CUDA" == "" ]; do
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read -p "Do you wish to build TensorFlow with GPU support? [y/N] " INPUT
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case $INPUT in
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[Yy]* ) echo "GPU support will be enabled for TensorFlow"; TF_NEED_CUDA=1;;
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[Nn]* ) echo "No GPU support will be enabled for TensorFlow"; TF_NEED_CUDA=0;;
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"" ) echo "No GPU support will be enabled for TensorFlow"; TF_NEED_CUDA=0;;
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* ) echo "Invalid selection: " $INPUT;;
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esac
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done
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if [ "$TF_NEED_CUDA" == "0" ]; then
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echo "Configuration finished"
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exit
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fi
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# Set up which gcc nvcc should use as the host compiler
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while true; do
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fromuser=""
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if [ -z "$GCC_HOST_COMPILER_PATH" ]; then
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default_gcc_host_compiler_path=$(which gcc)
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read -p "Please specify which gcc nvcc should use as the host compiler. [Default is $default_gcc_host_compiler_path]: " GCC_HOST_COMPILER_PATH
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fromuser="1"
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if [ -z "$GCC_HOST_COMPILER_PATH" ]; then
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GCC_HOST_COMPILER_PATH=$default_gcc_host_compiler_path
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fi
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fi
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if [ -e "$GCC_HOST_COMPILER_PATH" ]; then
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break
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fi
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echo "Invalid gcc path. ${GCC_HOST_COMPILER_PATH} cannot be found" 1>&2
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if [ -z "$fromuser" ]; then
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exit 1
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fi
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GCC_HOST_COMPILER_PATH=""
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# Retry
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done
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# Find out where the CUDA toolkit is installed
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while true; do
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# Configure the Cuda SDK version to use.
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if [ -z "$TF_CUDA_VERSION" ]; then
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read -p "Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: " TF_CUDA_VERSION
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fi
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fromuser=""
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if [ -z "$CUDA_TOOLKIT_PATH" ]; then
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default_cuda_path=/usr/local/cuda
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read -p "Please specify the location where CUDA $TF_CUDA_VERSION toolkit is installed. Refer to README.md for more details. [Default is $default_cuda_path]: " CUDA_TOOLKIT_PATH
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fromuser="1"
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if [ -z "$CUDA_TOOLKIT_PATH" ]; then
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CUDA_TOOLKIT_PATH=$default_cuda_path
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fi
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fi
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if [[ -z "$TF_CUDA_VERSION" ]]; then
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TF_CUDA_EXT=""
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else
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TF_CUDA_EXT=".$TF_CUDA_VERSION"
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fi
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if [ -e $CUDA_TOOLKIT_PATH/lib64/libcudart.so$TF_CUDA_EXT ]; then
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break
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fi
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echo "Invalid path to CUDA $TF_CUDA_VERSION toolkit. $CUDA_TOOLKIT_PATH/lib64/libcudart.so$TF_CUDA_EXT cannot be found"
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if [ -z "$fromuser" ]; then
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exit 1
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fi
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# Retry
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TF_CUDA_VERSION=""
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CUDA_TOOLKIT_PATH=""
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done
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# Find out where the cuDNN library is installed
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while true; do
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# Configure the Cudnn version to use.
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if [ -z "$TF_CUDNN_VERSION" ]; then
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read -p "Please specify the Cudnn version you want to use. [Leave empty to use system default]: " TF_CUDNN_VERSION
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fi
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fromuser=""
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if [ -z "$CUDNN_INSTALL_PATH" ]; then
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default_cudnn_path=${CUDA_TOOLKIT_PATH}
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read -p "Please specify the location where cuDNN $TF_CUDNN_VERSION library is installed. Refer to README.md for more details. [Default is $default_cudnn_path]: " CUDNN_INSTALL_PATH
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fromuser="1"
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if [ -z "$CUDNN_INSTALL_PATH" ]; then
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CUDNN_INSTALL_PATH=$default_cudnn_path
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fi
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# Result returned from "read" will be used unexpanded. That make "~" unuseable.
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# Going through one more level of expansion to handle that.
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CUDNN_INSTALL_PATH=$(bash -c "readlink -f $CUDNN_INSTALL_PATH")
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fi
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if [[ -z "$TF_CUDNN_VERSION" ]]; then
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TF_CUDNN_EXT=""
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else
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TF_CUDNN_EXT=".$TF_CUDNN_VERSION"
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fi
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if [ -e "$CUDNN_INSTALL_PATH/libcudnn.so${TF_CUDNN_EXT}" -o -e "$CUDNN_INSTALL_PATH/lib64/libcudnn.so${TF_CUDNN_EXT}" ]; then
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break
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fi
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CUDNN_PATH_FROM_LDCONFIG="$(ldconfig -p | sed -n 's/.*libcudnn.so .* => \(.*\)/\1/p')"
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if [ -e "${CUDNN_PATH_FROM_LDCONFIG}${TF_CUDNN_EXT}" ]; then
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CUDNN_INSTALL_PATH="$(dirname ${CUDNN_PATH_FROM_LDCONFIG})"
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break
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fi
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echo "Invalid path to cuDNN ${TF_CUDNN_VERSION} toolkit. Neither of the following two files can be found:"
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echo "$CUDNN_INSTALL_PATH/lib64/libcudnn.so${TF_CUDNN_EXT}"
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echo "$CUDNN_INSTALL_PATH/libcudnn.so${TF_CUDNN_EXT}"
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echo "${CUDNN_PATH_FROM_LDCONFIG}${TF_CUDNN_EXT}"
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if [ -z "$fromuser" ]; then
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exit 1
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fi
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# Retry
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TF_CUDNN_VERSION=""
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CUDNN_INSTALL_PATH=""
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done
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cat > third_party/gpus/cuda/cuda.config <<EOF
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# CUDA_TOOLKIT_PATH refers to the CUDA toolkit.
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CUDA_TOOLKIT_PATH="$CUDA_TOOLKIT_PATH"
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# CUDNN_INSTALL_PATH refers to the cuDNN toolkit. The cuDNN header and library
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# files can be either in this directory, or under include/ and lib64/
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# directories separately.
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CUDNN_INSTALL_PATH="$CUDNN_INSTALL_PATH"
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# The Cuda SDK version that should be used in this build (empty to use libcudart.so symlink)
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TF_CUDA_VERSION=$TF_CUDA_EXT
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# The Cudnn version that should be used in this build (empty to use libcudnn.so symlink)
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TF_CUDNN_VERSION=$TF_CUDNN_EXT
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EOF
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# Configure the gcc host compiler to use
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export WARNING=$DO_NOT_SUBMIT_WARNING
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perl -pi -e "s,CPU_COMPILER = \('.*'\),# \$ENV{WARNING}\nCPU_COMPILER = ('$GCC_HOST_COMPILER_PATH'),s" third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc
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perl -pi -e "s,GCC_HOST_COMPILER_PATH = \('.*'\),# \$ENV{WARNING}\nGCC_HOST_COMPILER_PATH = ('$GCC_HOST_COMPILER_PATH'),s" third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc
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# Configure the Cuda toolkit version to work with.
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perl -pi -e "s,CUDA_VERSION = \"[0-9\.]*\",CUDA_VERSION = \"$TF_CUDA_EXT\",s" tensorflow/core/platform/default/build_config.bzl
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perl -pi -e "s,(GetCudaVersion.*return )\"[0-9\.]*\",\1\"$TF_CUDA_EXT\",s" tensorflow/stream_executor/dso_loader.cc
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# Configure the Cudnn version to work with.
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perl -pi -e "s,CUDNN_VERSION = \"[0-9\.]*\",CUDNN_VERSION = \"$TF_CUDNN_EXT\",s" tensorflow/core/platform/default/build_config.bzl
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perl -pi -e "s,(GetCudnnVersion.*return )\"[0-9\.]*\",\1\"$TF_CUDNN_EXT\",s" tensorflow/stream_executor/dso_loader.cc
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# Configure the compute capabilities that TensorFlow builds for.
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# Since Cuda toolkit is not backward-compatible, this is not guaranteed to work.
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while true; do
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fromuser=""
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if [ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then
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cat << EOF
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Please specify a list of comma-separated Cuda compute capabilities you want to build with.
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You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
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Please note that each additional compute capability significantly increases your build time and binary size.
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EOF
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read -p "[Default is: \"3.5,5.2\"]: " TF_CUDA_COMPUTE_CAPABILITIES
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fromuser=1
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fi
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# Check whether all capabilities from the input is valid
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COMPUTE_CAPABILITIES=${TF_CUDA_COMPUTE_CAPABILITIES//,/ }
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ALL_VALID=1
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for CAPABILITY in $COMPUTE_CAPABILITIES; do
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if [[ ! "$CAPABILITY" =~ [0-9]+.[0-9]+ ]]; then
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echo "Invalid compute capability: " $CAPABILITY
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ALL_VALID=0
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break
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fi
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done
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if [ "$ALL_VALID" == "0" ]; then
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if [ -z "$fromuser" ]; then
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exit 1
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fi
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else
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break
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fi
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TF_CUDA_COMPUTE_CAPABILITIES=""
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done
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if [ ! -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then
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export WARNING=$DO_NOT_SUBMIT_WARNING
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function CudaGenCodeOpts() {
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OUTPUT=""
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for CAPABILITY in $@; do
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OUTPUT=${OUTPUT}" \"${CAPABILITY}\", "
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done
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echo $OUTPUT
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}
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export CUDA_GEN_CODES_OPTS=$(CudaGenCodeOpts ${TF_CUDA_COMPUTE_CAPABILITIES//,/ })
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perl -pi -0 -e 's,\n( *)([^\n]*supported_cuda_compute_capabilities\s*=\s*\[).*?(\]),\n\1# $ENV{WARNING}\n\1\2$ENV{CUDA_GEN_CODES_OPTS}\3,s' third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc
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function CudaVersionOpts() {
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OUTPUT=""
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for CAPABILITY in $@; do
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OUTPUT=$OUTPUT"CudaVersion(\"${CAPABILITY}\"), "
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done
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echo $OUTPUT
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}
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export CUDA_VERSION_OPTS=$(CudaVersionOpts ${TF_CUDA_COMPUTE_CAPABILITIES//,/ })
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perl -pi -0 -e 's,\n( *)([^\n]*supported_cuda_compute_capabilities\s*=\s*\{).*?(\}),\n\1// $ENV{WARNING}\n\1\2$ENV{CUDA_VERSION_OPTS}\3,s' tensorflow/core/common_runtime/gpu/gpu_device.cc
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fi
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# Invoke the cuda_config.sh and set up the TensorFlow's canonical view of the Cuda libraries
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(cd third_party/gpus/cuda; ./cuda_config.sh;) || exit -1
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echo "Configuration finished"
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