4316aeb4cb
* Run bazel clean and bazel fetch in the configure script even when building without GPU support to force clean+fetch if the user re-runs ./configure with a different setting. * Print a more actionable error messsage if the user attempts to build with --config=cuda but did not configure TensorFlow to build with GPU support. * Update the BUILD file in @local_config_cuda to use repository-local labels. Fixes #4105
312 lines
10 KiB
Bash
Executable File
312 lines
10 KiB
Bash
Executable File
#!/usr/bin/env bash
|
|
|
|
# Find out the absolute path to where ./configure resides
|
|
pushd `dirname $0` #> /dev/null
|
|
SOURCE_BASE_DIR=`pwd -P`
|
|
popd > /dev/null
|
|
|
|
function bazel_clean_and_fetch() {
|
|
bazel clean --expunge
|
|
bazel fetch //tensorflow/...
|
|
}
|
|
|
|
## Set up python-related environment settings
|
|
while true; do
|
|
fromuser=""
|
|
if [ -z "$PYTHON_BIN_PATH" ]; then
|
|
default_python_bin_path=$(which python)
|
|
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
|
|
|
|
while [ "$TF_NEED_GCP" == "" ]; do
|
|
read -p "Do you wish to build TensorFlow with "\
|
|
"Google Cloud Platform support? [y/N] " INPUT
|
|
case $INPUT in
|
|
[Yy]* ) echo "Google Cloud Platform support will be enabled for "\
|
|
"TensorFlow"; TF_NEED_GCP=1;;
|
|
[Nn]* ) echo "No Google Cloud Platform support will be enabled for "\
|
|
"TensorFlow"; TF_NEED_GCP=0;;
|
|
"" ) echo "No Google Cloud Platform support will be enabled for "\
|
|
"TensorFlow"; TF_NEED_GCP=0;;
|
|
* ) echo "Invalid selection: " $INPUT;;
|
|
esac
|
|
done
|
|
|
|
if [ "$TF_NEED_GCP" == "1" ]; then
|
|
|
|
## Verify that libcurl header files are available.
|
|
# Only check Linux, since on MacOS the header files are installed with XCode.
|
|
if [[ $(uname -a) =~ Linux ]] && [[ ! -f "/usr/include/curl/curl.h" ]]; then
|
|
echo "ERROR: It appears that the development version of libcurl is not "\
|
|
"available. Please install the libcurl3-dev package."
|
|
exit 1
|
|
fi
|
|
|
|
# Update Bazel build configuration.
|
|
perl -pi -e "s,WITH_GCP_SUPPORT = (False|True),WITH_GCP_SUPPORT = True,s" tensorflow/core/platform/default/build_config.bzl
|
|
else
|
|
# Update Bazel build configuration.
|
|
perl -pi -e "s,WITH_GCP_SUPPORT = (False|True),WITH_GCP_SUPPORT = False,s" tensorflow/core/platform/default/build_config.bzl
|
|
fi
|
|
|
|
while [ "$TF_NEED_HDFS" == "" ]; do
|
|
read -p "Do you wish to build TensorFlow with "\
|
|
"Hadoop File System support? [y/N] " INPUT
|
|
case $INPUT in
|
|
[Yy]* ) echo "Hadoop File System support will be enabled for "\
|
|
"TensorFlow"; TF_NEED_HDFS=1;;
|
|
[Nn]* ) echo "No Hadoop File System support will be enabled for "\
|
|
"TensorFlow"; TF_NEED_HDFS=0;;
|
|
"" ) echo "No Hadoop File System support will be enabled for "\
|
|
"TensorFlow"; TF_NEED_HDFS=0;;
|
|
* ) echo "Invalid selection: " $INPUT;;
|
|
esac
|
|
done
|
|
|
|
if [ "$TF_NEED_HDFS" == "1" ]; then
|
|
# Update Bazel build configuration.
|
|
perl -pi -e "s,WITH_HDFS_SUPPORT = (False|True),WITH_HDFS_SUPPORT = True,s" tensorflow/core/platform/default/build_config.bzl
|
|
else
|
|
# Update Bazel build configuration.
|
|
perl -pi -e "s,WITH_HDFS_SUPPORT = (False|True),WITH_HDFS_SUPPORT = False,s" tensorflow/core/platform/default/build_config.bzl
|
|
fi
|
|
|
|
## Find swig path
|
|
if [ -z "$SWIG_PATH" ]; then
|
|
SWIG_PATH=`type -p swig 2> /dev/null`
|
|
fi
|
|
if [[ ! -e "$SWIG_PATH" ]]; then
|
|
echo "Can't find swig. Ensure swig is in \$PATH or set \$SWIG_PATH."
|
|
exit 1
|
|
fi
|
|
echo "$SWIG_PATH" > tensorflow/tools/swig/swig_path
|
|
|
|
# Invoke python_config and set up symlinks to python includes
|
|
(./util/python/python_config.sh --setup "$PYTHON_BIN_PATH";) || exit -1
|
|
|
|
# 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 ${SOURCE_BASE_DIR}
|
|
|
|
## Set up Cuda-related environment settings
|
|
|
|
while [ "$TF_NEED_CUDA" == "" ]; do
|
|
read -p "Do you wish to build TensorFlow with GPU support? [y/N] " INPUT
|
|
case $INPUT in
|
|
[Yy]* ) echo "GPU support will be enabled for TensorFlow"; TF_NEED_CUDA=1;;
|
|
[Nn]* ) echo "No GPU support will be enabled for TensorFlow"; TF_NEED_CUDA=0;;
|
|
"" ) echo "No GPU support will be enabled for TensorFlow"; TF_NEED_CUDA=0;;
|
|
* ) echo "Invalid selection: " $INPUT;;
|
|
esac
|
|
done
|
|
|
|
export TF_NEED_CUDA
|
|
if [ "$TF_NEED_CUDA" == "0" ]; then
|
|
echo "Configuration finished"
|
|
bazel_clean_and_fetch
|
|
exit
|
|
fi
|
|
|
|
# Set up which gcc nvcc should use as the host compiler
|
|
while true; do
|
|
fromuser=""
|
|
if [ -z "$GCC_HOST_COMPILER_PATH" ]; then
|
|
default_gcc_host_compiler_path=$(which gcc)
|
|
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
|
|
OSNAME=`uname -s`
|
|
|
|
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
|
|
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=".$TF_CUDA_VERSION"
|
|
fi
|
|
|
|
if [ "$OSNAME" == "Linux" ]; then
|
|
CUDA_RT_LIB_PATH="lib64/libcudart.so${TF_CUDA_EXT}"
|
|
elif [ "$OSNAME" == "Darwin" ]; 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=""
|
|
# Resolve to the SONAME of the symlink. Use readlink without -f
|
|
# to resolve exactly once to the SONAME. E.g, libcudnn.so ->
|
|
# libcudnn.so.4
|
|
REALVAL=`readlink ${CUDNN_INSTALL_PATH}/lib64/libcudnn.so`
|
|
|
|
# Extract the version of the SONAME, if it was indeed symlinked to
|
|
# the SONAME version of the file.
|
|
if [[ "$REALVAL" =~ .so[.]+([0-9]*) ]];
|
|
then
|
|
TF_CUDNN_EXT="."${BASH_REMATCH[1]}
|
|
TF_CUDNN_VERSION=${BASH_REMATCH[1]}
|
|
echo "libcudnn.so resolves to libcudnn${TF_CUDNN_EXT}"
|
|
fi
|
|
else
|
|
TF_CUDNN_EXT=".$TF_CUDNN_VERSION"
|
|
fi
|
|
|
|
if [ "$OSNAME" == "Linux" ]; then
|
|
CUDA_DNN_LIB_PATH="lib64/libcudnn.so${TF_CUDNN_EXT}"
|
|
CUDA_DNN_LIB_ALT_PATH="libcudnn.so${TF_CUDNN_EXT}"
|
|
elif [ "$OSNAME" == "Darwin" ]; 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 [ "$OSNAME" == "Linux" ]; then
|
|
CUDNN_PATH_FROM_LDCONFIG="$(ldconfig -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}/${CUDA_DNN_LIB_ALT_PATH}"
|
|
if [ "$OSNAME" == "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
|
|
|
|
bazel_clean_and_fetch
|
|
|
|
echo "Configuration finished"
|