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Diffstat (limited to 'third_party/gpus/cuda/cuda_config.sh')
| -rwxr-xr-x | third_party/gpus/cuda/cuda_config.sh | 234 |
1 files changed, 0 insertions, 234 deletions
diff --git a/third_party/gpus/cuda/cuda_config.sh b/third_party/gpus/cuda/cuda_config.sh deleted file mode 100755 index 8a0c70cbbd..0000000000 --- a/third_party/gpus/cuda/cuda_config.sh +++ /dev/null @@ -1,234 +0,0 @@ -#!/usr/bin/env bash -# Copyright 2015 The TensorFlow Authors. All Rights Reserved. -# -# 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 -# -# http://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. -# ============================================================================== - - -# A simple script to configure the Cuda tree needed for the TensorFlow GPU -# build. We need both Cuda toolkit $TF_CUDA_VERSION and Cudnn $TF_CUDNN_VERSION. -# Useage: -# * User edit cuda.config to point both Cuda toolkit and Cudnn libraries to their local path -# * run cuda_config.sh to generate symbolic links in the source tree to reflect -# * the file organizations needed by TensorFlow. - -print_usage() { -cat << EOF -Usage: $0 [--check] - Configure TensorFlow's canonical view of Cuda libraries using cuda.config. -Arguments: - --check: Only check that the proper Cuda dependencies has already been - properly configured in the source tree. It also creates symbolic links to - the files in the gen-tree to make bazel happy. -EOF -} - -CHECK_ONLY=0 -# Parse the arguments. Add more arguments as the "case" line when needed. -while [[ $# -gt 0 ]]; do - argument="$1" - shift - case $argument in - --check) - CHECK_ONLY=1 - ;; - *) - echo "Error: unknown arguments" - print_usage - exit -1 - ;; - esac -done - -source cuda.config || exit -1 - -OUTPUTDIR=${OUTPUTDIR:-../../..} -CUDA_TOOLKIT_PATH=${CUDA_TOOLKIT_PATH:-/usr/local/cuda} -CUDNN_INSTALL_BASEDIR=${CUDNN_INSTALL_PATH:-/usr/local/cuda} - -if [[ -z "$TF_CUDA_VERSION" ]]; then - TF_CUDA_EXT="" -else - TF_CUDA_EXT=".$TF_CUDA_VERSION" -fi - -if [[ -z "$TF_CUDNN_VERSION" ]]; then - TF_CUDNN_EXT="" -else - TF_CUDNN_EXT=".$TF_CUDNN_VERSION" -fi - -# An error message when the Cuda toolkit is not found -function CudaError { - echo ERROR: $1 -cat << EOF -############################################################################## -############################################################################## -Cuda $TF_CUDA_VERSION toolkit is missing. -1. Download and install the CUDA $TF_CUDA_VERSION toolkit and CUDNN $TF_CUDNN_VERSION library; -2. Run configure from the root of the source tree, before rerunning bazel; -Please refer to README.md for more details. -############################################################################## -############################################################################## -EOF - exit -1 -} - -# An error message when CUDNN is not found -function CudnnError { - echo ERROR: $1 -cat << EOF -############################################################################## -############################################################################## -Cudnn $TF_CUDNN_VERSION is missing. -1. Download and install the CUDA $TF_CUDA_VERSION toolkit and CUDNN $TF_CUDNN_VERSION library; -2. Run configure from the root of the source tree, before rerunning bazel; -Please refer to README.md for more details. -############################################################################## -############################################################################## -EOF - exit -1 -} - -# Check that Cuda libraries has already been properly configured in the source tree. -# We still need to create links to the gen-tree to make bazel happy. -function CheckAndLinkToSrcTree { - ERROR_FUNC=$1 - FILE=$2 - if test ! -e $FILE; then - $ERROR_FUNC "$PWD/$FILE cannot be found" - fi - - # Link the output file to the source tree, avoiding self links if they are - # the same. This could happen if invoked from the source tree by accident. - if [ ! $($READLINK_CMD -f $PWD) == $($READLINK_CMD -f $OUTPUTDIR/third_party/gpus/cuda) ]; then - mkdir -p $(dirname $OUTPUTDIR/third_party/gpus/cuda/$FILE) - ln -sf $PWD/$FILE $OUTPUTDIR/third_party/gpus/cuda/$FILE - fi -} - -OSNAME=`uname -s` -if [ "$OSNAME" == "Linux" ]; then - CUDA_LIB_PATH="lib64" - CUDA_CUPTI_LIB_DIR="extras/CUPTI/lib64" - CUDA_RT_LIB_PATH="lib64/libcudart.so${TF_CUDA_EXT}" - CUDA_RT_LIB_STATIC_PATH="lib64/libcudart_static.a" - CUDA_BLAS_LIB_PATH="lib64/libcublas.so${TF_CUDA_EXT}" - CUDA_DNN_LIB_PATH="lib64/libcudnn.so${TF_CUDNN_EXT}" - CUDA_DNN_LIB_ALT_PATH="libcudnn.so${TF_CUDNN_EXT}" - CUDA_FFT_LIB_PATH="lib64/libcufft.so${TF_CUDA_EXT}" - CUDA_CUPTI_LIB_PATH="extras/CUPTI/lib64/libcupti.so${TF_CUDA_EXT}" - READLINK_CMD="readlink" -elif [ "$OSNAME" == "Darwin" ]; then - CUDA_LIB_PATH="lib" - CUDA_CUPTI_LIB_DIR="extras/CUPTI/lib" - CUDA_RT_LIB_PATH="lib/libcudart${TF_CUDA_EXT}.dylib" - CUDA_RT_LIB_STATIC_PATH="lib/libcudart_static.a" - CUDA_BLAS_LIB_PATH="lib/libcublas${TF_CUDA_EXT}.dylib" - CUDA_DNN_LIB_PATH="lib/libcudnn${TF_CUDNN_EXT}.dylib" - CUDA_DNN_LIB_ALT_PATH="libcudnn${TF_CUDNN_EXT}.dylib" - CUDA_FFT_LIB_PATH="lib/libcufft${TF_CUDA_EXT}.dylib" - CUDA_CUPTI_LIB_PATH="extras/CUPTI/lib/libcupti${TF_CUDA_EXT}.dylib" - READLINK_CMD="greadlink" -fi - -if [ "$CHECK_ONLY" == "1" ]; then - CheckAndLinkToSrcTree CudaError include/cuda.h - CheckAndLinkToSrcTree CudaError include/cublas.h - CheckAndLinkToSrcTree CudnnError include/cudnn.h - CheckAndLinkToSrcTree CudaError extras/CUPTI/include/cupti.h - CheckAndLinkToSrcTree CudaError $CUDA_RT_LIB_STATIC_PATH - CheckAndLinkToSrcTree CudaError $CUDA_BLAS_LIB_PATH - CheckAndLinkToSrcTree CudnnError $CUDA_DNN_LIB_PATH - CheckAndLinkToSrcTree CudaError $CUDA_RT_LIB_PATH - CheckAndLinkToSrcTree CudaError $CUDA_FFT_LIB_PATH - CheckAndLinkToSrcTree CudaError $CUDA_CUPTI_LIB_PATH - exit 0 -fi - -# Actually configure the source tree for TensorFlow's canonical view of Cuda -# libraries. - -if test ! -e ${CUDA_TOOLKIT_PATH}/${CUDA_RT_LIB_PATH}; then - CudaError "cannot find ${CUDA_TOOLKIT_PATH}/${CUDA_RT_LIB_PATH}" -fi - -if test ! -e ${CUDA_TOOLKIT_PATH}/${CUDA_CUPTI_LIB_PATH}; then - CudaError "cannot find ${CUDA_TOOLKIT_PATH}/${CUDA_CUPTI_LIB_PATH}" -fi - -if test ! -d ${CUDNN_INSTALL_BASEDIR}; then - CudnnError "cannot find dir: ${CUDNN_INSTALL_BASEDIR}" -fi - -# Locate cudnn.h -if test -e ${CUDNN_INSTALL_BASEDIR}/cudnn.h; then - CUDNN_HEADER_DIR=${CUDNN_INSTALL_BASEDIR} -elif test -e ${CUDNN_INSTALL_BASEDIR}/include/cudnn.h; then - CUDNN_HEADER_DIR=${CUDNN_INSTALL_BASEDIR}/include -elif test -e /usr/include/cudnn.h; then - CUDNN_HEADER_DIR=/usr/include -else - CudnnError "cannot find cudnn.h under: ${CUDNN_INSTALL_BASEDIR}" -fi - -# Locate libcudnn -if test -e ${CUDNN_INSTALL_BASEDIR}/${CUDA_DNN_LIB_PATH}; then - CUDNN_LIB_INSTALL_PATH=${CUDNN_INSTALL_BASEDIR}/${CUDA_DNN_LIB_PATH} -elif test -e ${CUDNN_INSTALL_BASEDIR}/${CUDA_DNN_LIB_ALT_PATH}; then - CUDNN_LIB_INSTALL_PATH=${CUDNN_INSTALL_BASEDIR}/${CUDA_DNN_LIB_ALT_PATH} -else - CudnnError "cannot find ${CUDA_DNN_LIB_PATH} or ${CUDA_DNN_LIB_ALT_PATH} under: ${CUDNN_INSTALL_BASEDIR}" -fi - -# Helper function to build symbolic links for all files under a directory. -function LinkOneDir { - SRC_PREFIX=$1 - DST_PREFIX=$2 - SRC_DIR=$3 - DST_DIR=$(echo $SRC_DIR | sed "s,^$SRC_PREFIX,$DST_PREFIX,") - mkdir -p $DST_DIR - FILE_LIST=$(find -L $SRC_DIR -maxdepth 1 -type f) - if test "$FILE_LIST" != ""; then - ln -sf $FILE_LIST $DST_DIR/ || exit -1 - fi -} -export -f LinkOneDir - -# Build links for all files under the directory, including subdirectoreis. -function LinkAllFiles { - SRC_DIR=$1 - DST_DIR=$2 - find -L $SRC_DIR -type d | xargs -I {} bash -c "LinkOneDir $SRC_DIR $DST_DIR {}" || exit -1 -} - -# Set up the symbolic links for cuda toolkit. We link at individual file level, -# not at the directory level. -# This is because the external library may have different file layout from our desired structure. -mkdir -p $OUTPUTDIR/third_party/gpus/cuda -echo "Setting up Cuda include" -LinkAllFiles ${CUDA_TOOLKIT_PATH}/include $OUTPUTDIR/third_party/gpus/cuda/include || exit -1 -echo "Setting up Cuda ${CUDA_LIB_PATH}" -LinkAllFiles ${CUDA_TOOLKIT_PATH}/${CUDA_LIB_PATH} $OUTPUTDIR/third_party/gpus/cuda/${CUDA_LIB_PATH} || exit -1 -echo "Setting up Cuda bin" -LinkAllFiles ${CUDA_TOOLKIT_PATH}/bin $OUTPUTDIR/third_party/gpus/cuda/bin || exit -1 -echo "Setting up Cuda nvvm" -LinkAllFiles ${CUDA_TOOLKIT_PATH}/nvvm $OUTPUTDIR/third_party/gpus/cuda/nvvm || exit -1 -echo "Setting up CUPTI include" -LinkAllFiles ${CUDA_TOOLKIT_PATH}/extras/CUPTI/include $OUTPUTDIR/third_party/gpus/cuda/extras/CUPTI/include || exit -1 -echo "Setting up CUPTI lib64" -LinkAllFiles ${CUDA_TOOLKIT_PATH}/${CUDA_CUPTI_LIB_DIR} $OUTPUTDIR/third_party/gpus/cuda/${CUDA_CUPTI_LIB_DIR} || exit -1 - -# Set up symbolic link for cudnn -ln -sf $CUDNN_HEADER_DIR/cudnn.h $OUTPUTDIR/third_party/gpus/cuda/include/cudnn.h || exit -1 -ln -sf $CUDNN_LIB_INSTALL_PATH $OUTPUTDIR/third_party/gpus/cuda/$CUDA_DNN_LIB_PATH || exit -1 |