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configure.sh 5.41 KB
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Michael Broughton 提交于 2021-02-05 13:11 +08:00 . Upgrade nightly builds to tf 2.4.1.
#!/bin/bash
# Copyright 2020 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.
# ==============================================================================
PLATFORM="$(uname -s | tr 'A-Z' 'a-z')"
function write_to_bazelrc() {
echo "$1" >> .bazelrc
}
function write_action_env_to_bazelrc() {
write_to_bazelrc "build --action_env $1=\"$2\""
}
function write_linkopt_dir_to_bazelrc() {
write_to_bazelrc "build --linkopt -Wl,-rpath,$1" >> .bazelrc
}
function is_linux() {
[[ "${PLATFORM}" == "linux" ]]
}
function is_macos() {
[[ "${PLATFORM}" == "darwin" ]]
}
function is_windows() {
# On windows, the shell script is actually running in msys
[[ "${PLATFORM}" =~ msys_nt*|mingw*|cygwin*|uwin* ]]
}
function is_ppc64le() {
[[ "$(uname -m)" == "ppc64le" ]]
}
# Remove .bazelrc if it already exist
[ -e .bazelrc ] && rm .bazelrc
# Check if we are building GPU or CPU ops, default CPU
while [[ "$TF_NEED_CUDA" == "" ]]; do
read -p "Do you want to build ops again TensorFlow CPU pip package?"\
" Y or enter for CPU (tensorflow-cpu), N for GPU (tensorflow). [Y/n] " INPUT
case $INPUT in
[Yy]* ) echo "Build with CPU pip package."; TF_NEED_CUDA=0;;
[Nn]* ) echo "Build with GPU pip package."; TF_NEED_CUDA=1;;
"" ) echo "Build with CPU pip package."; TF_NEED_CUDA=0;;
* ) echo "Invalid selection: " $INPUT;;
esac
done
while [[ "$TF_CUDA_VERSION" == "" ]]; do
read -p "Are you building against TensorFlow 2.1(including RCs) or newer?[Y/n] " INPUT
case $INPUT in
[Yy]* ) echo "Build against TensorFlow 2.1 or newer."; TF_CUDA_VERSION=10.1;;
[Nn]* ) echo "Build against TensorFlow <2.1."; TF_CUDA_VERSION=10.0;;
"" ) echo "Build against TensorFlow 2.1 or newer."; TF_CUDA_VERSION=10.1;;
* ) echo "Invalid selection: " $INPUT;;
esac
done
# Check if it's installed
if [[ $(pip show tensorflow) == *tensorflow* ]] || [[ $(pip show tf-nightly) == *tf-nightly* ]]; then
echo 'Using installed tensorflow'
else
# Uninstall CPU version if it is installed.
if [[ $(pip show tensorflow-cpu) == *tensorflow-cpu* ]]; then
echo 'Already have tensorflow non-gpu installed. Uninstalling......\n'
pip uninstall tensorflow
elif [[ $(pip show tf-nightly-cpu) == *tf-nightly-cpu* ]]; then
echo 'Already have tensorflow non-gpu installed. Uninstalling......\n'
pip uninstall tf-nightly
fi
# Install GPU version
echo 'Installing tensorflow .....\n'
pip install tensorflow
fi
TF_CFLAGS=( $(python -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_compile_flags()))') )
TF_LFLAGS="$(python -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_link_flags()))')"
write_to_bazelrc "build:cuda --define=using_cuda=true --define=using_cuda_nvcc=true"
if [[ "$PIP_MANYLINUX2010" == "0" ]]; then
write_to_bazelrc "build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain"
fi
write_to_bazelrc "build --spawn_strategy=standalone"
write_to_bazelrc "build --strategy=Genrule=standalone"
write_to_bazelrc "build --experimental_repo_remote_exec"
write_to_bazelrc "build -c opt"
write_to_bazelrc "build --cxxopt=\"-D_GLIBCXX_USE_CXX11_ABI=0\""
if is_windows; then
# Use pywrap_tensorflow instead of tensorflow_framework on Windows
SHARED_LIBRARY_DIR=${TF_CFLAGS:2:-7}"python"
else
SHARED_LIBRARY_DIR=${TF_LFLAGS:2}
fi
SHARED_LIBRARY_NAME=$(echo $TF_LFLAGS | rev | cut -d":" -f1 | rev)
if ! [[ $TF_LFLAGS =~ .*:.* ]]; then
if is_macos; then
SHARED_LIBRARY_NAME="libtensorflow_framework.dylib"
elif is_windows; then
# Use pywrap_tensorflow's import library on Windows. It is in the same dir as the dll/pyd.
SHARED_LIBRARY_NAME="_pywrap_tensorflow_internal.lib"
else
SHARED_LIBRARY_NAME="libtensorflow_framework.so"
fi
fi
HEADER_DIR=${TF_CFLAGS:2}
if is_windows; then
SHARED_LIBRARY_DIR=${SHARED_LIBRARY_DIR//\\//}
SHARED_LIBRARY_NAME=${SHARED_LIBRARY_NAME//\\//}
HEADER_DIR=${HEADER_DIR//\\//}
fi
write_action_env_to_bazelrc "TF_HEADER_DIR" ${HEADER_DIR}
write_action_env_to_bazelrc "TF_SHARED_LIBRARY_DIR" ${SHARED_LIBRARY_DIR}
write_action_env_to_bazelrc "TF_SHARED_LIBRARY_NAME" ${SHARED_LIBRARY_NAME}
write_action_env_to_bazelrc "TF_NEED_CUDA" ${TF_NEED_CUDA}
if ! is_windows; then
write_linkopt_dir_to_bazelrc ${SHARED_LIBRARY_DIR}
fi
# TODO(yifeif): do not hardcode path
if [[ "$TF_NEED_CUDA" == "1" ]]; then
write_action_env_to_bazelrc "TF_CUDA_VERSION" ${TF_CUDA_VERSION}
write_action_env_to_bazelrc "TF_CUDNN_VERSION" "7"
if is_windows; then
write_action_env_to_bazelrc "CUDNN_INSTALL_PATH" "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${TF_CUDA_VERSION}"
write_action_env_to_bazelrc "CUDA_TOOLKIT_PATH" "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${TF_CUDA_VERSION}"
else
write_action_env_to_bazelrc "CUDNN_INSTALL_PATH" "/usr/lib/x86_64-linux-gnu"
write_action_env_to_bazelrc "CUDA_TOOLKIT_PATH" "/usr/local/cuda"
fi
write_to_bazelrc "build --config=cuda"
write_to_bazelrc "test --config=cuda"
fi
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