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configure.py
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configure.py
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# 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 .
# ==============================================================================
# Usage: python configure.py
#
import os
import pathlib
import platform
import logging
import tensorflow as tf
_TFRA_BAZELRC = ".bazelrc"
# Maping TensorFlow version to valid Bazel version.
_VALID_BAZEL_VERSION = {"1.15.2": "0.26.1", "2.4.1": "3.1.0"}
# Writes variables to bazelrc file
def write(line):
with open(_TFRA_BAZELRC, "a") as f:
f.write(line + "\n")
def write_action_env(var_name, var):
write('build --action_env {}="{}"'.format(var_name, var))
def is_macos():
return platform.system() == "Darwin"
def is_windows():
return platform.system() == "Windows"
def is_linux():
return platform.system() == "Linux"
def is_raspi_arm():
return os.uname()[4] == "armv7l"
def get_tf_header_dir():
if get_tf_version_integer() >= 2000:
tf_header_dir = tf.sysconfig.get_compile_flags()[0][2:]
if is_windows():
tf_header_dir = tf_header_dir.replace("\\", "/")
else:
current_path = os.path.dirname(os.path.abspath(__file__))
tf_header_dir = "{}/build_deps/tf_header/{}/tensorflow".format(
current_path, tf.__version__)
return tf_header_dir
def get_tf_shared_lib_dir():
# OS Specific parsing
if is_windows():
tf_shared_lib_dir = tf.sysconfig.get_compile_flags()[0][2:-7] + "python"
return tf_shared_lib_dir.replace("\\", "/")
elif is_raspi_arm():
return tf.sysconfig.get_compile_flags()[0][2:-7] + "python"
else:
return tf.sysconfig.get_link_flags()[0][2:]
# Converts the linkflag namespec to the full shared library name
def get_shared_lib_name():
namespec = tf.sysconfig.get_link_flags()
if is_macos():
# MacOS
return "libtensorflow_framework.dylib"
elif is_windows():
# Windows
return "_pywrap_tensorflow_internal.lib"
elif is_raspi_arm():
# The below command for linux would return an empty list
return "_pywrap_tensorflow_internal.so"
else:
# Linux
return namespec[1][3:]
def get_tf_version_integer():
"""
Get Tensorflow version as a 4 digits string.
For example:
1.15.2 get 1152
2.4.1 get 2041
The 4-digits-string will be passed to C macro to discriminate different
Tensorflow versions.
We assume that major version has 1 digit, minor version has 2 digits. And
patch version has 1 digit.
"""
try:
version = tf.__version__
except AttributeError:
raise ImportError(
'\nPlease install a TensorFlow on your compiling machine, '
'The compiler needs to know the version of Tensorflow '
'and get TF c++ headers according to the installed TensorFlow. '
'\nNote: Only TensorFlow 2.4.1, 1.15.2 are supported.')
try:
major, minor, patch = version.split('.')
assert len(
major
) == 1, "Tensorflow major version must be length of 1. Version: {}".format(
version)
assert len(
minor
) <= 2, "Tensorflow minor version must be less or equal to 2. Version: {}".format(
version)
assert len(
patch
) == 1, "Tensorflow patch version must be length of 1. Version: {}".format(
version)
except:
raise ValueError('got wrong tf.__version__: {}'.format(version))
tf_version_num = str(int(major) * 1000 + int(minor) * 10 + int(patch))
if len(tf_version_num) != 4:
raise ValueError('Tensorflow version flag must be length of 4 (major'
' version: 1, minor version: 2, patch_version: 1). But'
' get: {}'.format(tf_version_num))
return int(tf_version_num)
def check_bazel_version():
stream = os.popen('bazel version |grep label')
output = stream.read()
installed_bazel_version = str(output).split(":")[1].strip()
valid_bazel_version = _VALID_BAZEL_VERSION[tf.__version__]
if installed_bazel_version != valid_bazel_version:
raise ValueError('Bazel version is {}, but {} is needed.'.format(
installed_bazel_version, valid_bazel_version))
def extract_tf_header():
tf_header_dir = get_tf_header_dir()
tf_version_integer = get_tf_version_integer()
if tf_version_integer < 2000:
_output_dir = tf_header_dir[:-(len("1.15.2/tensorflow"))]
_tar_path = tf_header_dir.replace("/tensorflow", ".tar.gz")
_cmd = "tar -zxvf {} --directory {} >/dev/null 2>&1".format(
_tar_path, _output_dir)
ret = os.system(_cmd)
if ret != 0:
raise ValueError(
'Error happened when decompressing TF headers tar file:{}.'.format(
_tar_path))
def create_build_configuration():
print()
print("Configuring TensorFlow Recommenders-Addons to be built from source...")
if os.path.isfile(_TFRA_BAZELRC):
os.remove(_TFRA_BAZELRC)
if is_linux():
check_bazel_version()
extract_tf_header()
logging.disable(logging.WARNING)
write_action_env("TF_HEADER_DIR", get_tf_header_dir())
write_action_env("TF_SHARED_LIBRARY_DIR", get_tf_shared_lib_dir())
write_action_env("TF_SHARED_LIBRARY_NAME", get_shared_lib_name())
write_action_env("TF_CXX11_ABI_FLAG", tf.sysconfig.CXX11_ABI_FLAG)
tf_version_integer = get_tf_version_integer()
# This is used to trace the difference between Tensorflow versions.
write_action_env("TF_VERSION_INTEGER", tf_version_integer)
write_action_env("FOR_TF_SERVING", os.getenv("FOR_TF_SERVING", "0"))
write("build --spawn_strategy=standalone")
write("build --strategy=Genrule=standalone")
write("build -c opt")
if is_windows():
write("build --config=windows")
write("build:windows --enable_runfiles")
write("build:windows --copt=/experimental:preprocessor")
write("build:windows --host_copt=/experimental:preprocessor")
write("build:windows --copt=/arch=AVX")
if is_macos() or is_linux():
write("build --copt=-mavx")
if os.getenv("TF_NEED_CUDA", "0") == "1":
print("> Building GPU & CPU ops")
configure_cuda()
else:
print("> Building only CPU ops")
print()
print("Build configurations successfully written to", _TFRA_BAZELRC, ":\n")
print(pathlib.Path(_TFRA_BAZELRC).read_text())
def configure_cuda():
write_action_env("TF_NEED_CUDA", "1")
write_action_env("CUDA_TOOLKIT_PATH",
os.getenv("CUDA_TOOLKIT_PATH", "/usr/local/cuda"))
write_action_env(
"CUDNN_INSTALL_PATH",
os.getenv("CUDNN_INSTALL_PATH", "/usr/lib/x86_64-linux-gnu"),
)
write_action_env("TF_CUDA_VERSION", os.getenv("TF_CUDA_VERSION", "11.0"))
write_action_env("TF_CUDNN_VERSION", os.getenv("TF_CUDNN_VERSION", "8.0"))
write("test --config=cuda")
write("build --config=cuda")
write("build:cuda --define=using_cuda=true --define=using_cuda_nvcc=true")
write("build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain")
if __name__ == "__main__":
create_build_configuration()