tensorflow/tools/pip_package/setup.py - platform/external/tensorflow - Git at Google

 # 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.
 # ==============================================================================
 """TensorFlow is an open source machine learning framework for everyone.

 TensorFlow is an open source software library for high performance numerical
 computation. Its flexible architecture allows easy deployment of computation
 across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters
 of servers to mobile and edge devices.

 Originally developed by researchers and engineers from the Google Brain team
 within Google's AI organization, it comes with strong support for machine
 learning and deep learning and the flexible numerical computation core is used
 across many other scientific domains.
 """

 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function

 import fnmatch
 import os
 import re
 import sys

 from setuptools import Command
 from setuptools import find_packages
 from setuptools import setup
 from setuptools.command.install import install as InstallCommandBase
 from setuptools.dist import Distribution

 DOCLINES = __doc__.split('\n')

 # This version string is semver compatible, but incompatible with pip.
 # For pip, we will remove all '-' characters from this string, and use the
 # result for pip.
 # Also update tensorflow/tensorflow.bzl and
 # tensorflow/core/public/version.h
 _VERSION = '1.14.0'

 REQUIRED_PACKAGES = [
     'absl-py >= 0.7.0',
     'astor >= 0.6.0',
     'backports.weakref >= 1.0rc1;python_version<"3.4"',
     'enum34 >= 1.1.6;python_version<"3.4"',
     'gast == 0.2.2',
     'google_pasta >= 0.1.6',
     'keras_applications >= 1.0.8',
     'keras_preprocessing >= 1.0.5',
     'numpy >= 1.16.0, < 2.0',
     'opt_einsum >= 2.3.2',
     'six >= 1.10.0',
     'protobuf >= 3.6.1',
     'tensorboard >= 1.15.0, < 1.16.0',
     'tensorflow_estimator >= 1.14.0rc0, < 1.15.0rc0',
     'termcolor >= 1.1.0',
     'wrapt >= 1.11.1',
     # python3 requires wheel 0.26
     'wheel >= 0.26;python_version>="3"',
     'wheel;python_version<"3"',
     # mock comes with unittest.mock for python3, need to install for python2
     'mock >= 2.0.0;python_version<"3"',
     # functools comes with python3, need to install the backport for python2
     'functools32 >= 3.2.3;python_version<"3"',
 ]

 if sys.byteorder == 'little':
   # grpcio does not build correctly on big-endian machines due to lack of
   # BoringSSL support.
   # See https://github.com/tensorflow/tensorflow/issues/17882.
   REQUIRED_PACKAGES.append('grpcio >= 1.8.6')

 project_name = 'tensorflow'
 if '--project_name' in sys.argv:
   project_name_idx = sys.argv.index('--project_name')
   project_name = sys.argv[project_name_idx + 1]
   sys.argv.remove('--project_name')
   sys.argv.pop(project_name_idx)

 # tf-nightly should depend on tb-nightly
 if 'tf_nightly' in project_name:
   for i, pkg in enumerate(REQUIRED_PACKAGES):
     if 'tensorboard' in pkg:
       REQUIRED_PACKAGES[i] = 'tb-nightly >= 2.0.0a0, < 2.1.0a0'
     elif 'tensorflow_estimator' in pkg and '2.0' in project_name:
       REQUIRED_PACKAGES[i] = 'tensorflow-estimator-2.0-preview'
     elif 'tensorflow_estimator' in pkg:
       REQUIRED_PACKAGES[i] = 'tf-estimator-nightly'

 # pylint: disable=line-too-long
 CONSOLE_SCRIPTS = [
     'toco_from_protos = tensorflow.lite.toco.python.toco_from_protos:main',
     'tflite_convert = tensorflow.lite.python.tflite_convert:main',
     'toco = tensorflow.lite.python.tflite_convert:main',
     'saved_model_cli = tensorflow.python.tools.saved_model_cli:main',
     # We need to keep the TensorBoard command, even though the console script
     # is now declared by the tensorboard pip package. If we remove the
     # TensorBoard command, pip will inappropriately remove it during install,
     # even though the command is not removed, just moved to a different wheel.
     'tensorboard = tensorboard.main:run_main',
     'tf_upgrade_v2 = tensorflow.tools.compatibility.tf_upgrade_v2_main:main',
     'estimator_ckpt_converter = tensorflow_estimator.python.estimator.tools.checkpoint_converter:main',
 ]
 # pylint: enable=line-too-long

 # Only keep freeze_graph console script in 1.X.
 if _VERSION.startswith('1.') and '_2.0' not in project_name:
   CONSOLE_SCRIPTS.append(
       'freeze_graph = tensorflow.python.tools.freeze_graph:run_main')

 # remove the tensorboard console script if building tf_nightly
 if 'tf_nightly' in project_name:
   CONSOLE_SCRIPTS.remove('tensorboard = tensorboard.main:run_main')

 TEST_PACKAGES = [
     'scipy >= 0.15.1',
 ]


 class BinaryDistribution(Distribution):

   def has_ext_modules(self):
     return True


 class InstallCommand(InstallCommandBase):
   """Override the dir where the headers go."""

   def finalize_options(self):
     ret = InstallCommandBase.finalize_options(self)
     self.install_headers = os.path.join(self.install_purelib, 'tensorflow_core',
                                         'include')
     self.install_lib = self.install_platlib
     return ret


 class InstallHeaders(Command):
   """Override how headers are copied.

   The install_headers that comes with setuptools copies all files to
   the same directory. But we need the files to be in a specific directory
   hierarchy for -I <include_dir> to work correctly.
   """
   description = 'install C/C++ header files'

   user_options = [('install-dir=', 'd',
                    'directory to install header files to'),
                   ('force', 'f',
                    'force installation (overwrite existing files)'),
                  ]

   boolean_options = ['force']

   def initialize_options(self):
     self.install_dir = None
     self.force = 0
     self.outfiles = []

   def finalize_options(self):
     self.set_undefined_options('install',
                                ('install_headers', 'install_dir'),
                                ('force', 'force'))

   def mkdir_and_copy_file(self, header):
     install_dir = os.path.join(self.install_dir, os.path.dirname(header))
     # Get rid of some extra intervening directories so we can have fewer
     # directories for -I
     install_dir = re.sub('/google/protobuf_archive/src', '', install_dir)
     install_dir = re.sub('/include/tensorflow_core/', '/include/tensorflow/',
                          install_dir)

     # Copy external code headers into tensorflow_core/include.
     # A symlink would do, but the wheel file that gets created ignores
     # symlink within the directory hierarchy.
     # NOTE(keveman): Figure out how to customize bdist_wheel package so
     # we can do the symlink.
     external_header_locations = [
         'tensorflow_core/include/external/eigen_archive/',
         'tensorflow_core/include/external/com_google_absl/',
     ]
     for location in external_header_locations:
       if location in install_dir:
         extra_dir = install_dir.replace(location, '')
         if not os.path.exists(extra_dir):
           self.mkpath(extra_dir)
         self.copy_file(header, extra_dir)

     if not os.path.exists(install_dir):
       self.mkpath(install_dir)
     return self.copy_file(header, install_dir)

   def run(self):
     hdrs = self.distribution.headers
     if not hdrs:
       return

     self.mkpath(self.install_dir)
     for header in hdrs:
       (out, _) = self.mkdir_and_copy_file(header)
       self.outfiles.append(out)

   def get_inputs(self):
     return self.distribution.headers or []

   def get_outputs(self):
     return self.outfiles


 def find_files(pattern, root):
   """Return all the files matching pattern below root dir."""
   for dirpath, _, files in os.walk(root):
     for filename in fnmatch.filter(files, pattern):
       yield os.path.join(dirpath, filename)


 so_lib_paths = [
     i for i in os.listdir('.')
     if os.path.isdir(i) and fnmatch.fnmatch(i, '_solib_*')
 ]

 matches = []
 for path in so_lib_paths:
   matches.extend(
       ['../' + x for x in find_files('*', path) if '.py' not in x]
   )

 if os.name == 'nt':
   EXTENSION_NAME = 'python/_pywrap_tensorflow_internal.pyd'
 else:
   EXTENSION_NAME = 'python/_pywrap_tensorflow_internal.so'

 headers = (
     list(find_files('*.h', 'tensorflow_core/core')) +
     list(find_files('*.h', 'tensorflow_core/stream_executor')) +
     list(find_files('*.h', 'google/com_google_protobuf/src')) +
     list(find_files('*.inc', 'google/com_google_protobuf/src')) +
     list(find_files('*', 'third_party/eigen3')) + list(
         find_files('*.h', 'tensorflow_core/include/external/com_google_absl')) +
     list(
         find_files('*.inc', 'tensorflow_core/include/external/com_google_absl'))
     + list(find_files('*', 'tensorflow_core/include/external/eigen_archive')))

 setup(
     name=project_name,
     version=_VERSION.replace('-', ''),
     description=DOCLINES[0],
     long_description='\n'.join(DOCLINES[2:]),
     url='https://www.tensorflow.org/',
     download_url='https://github.com/tensorflow/tensorflow/tags',
     author='Google Inc.',
     author_email='packages@tensorflow.org',
     # Contained modules and scripts.
     packages=find_packages(),
     entry_points={
         'console_scripts': CONSOLE_SCRIPTS,
     },
     headers=headers,
     install_requires=REQUIRED_PACKAGES,
     tests_require=REQUIRED_PACKAGES + TEST_PACKAGES,
     # Add in any packaged data.
     include_package_data=True,
     package_data={
         'tensorflow': [
             EXTENSION_NAME,
         ] + matches,
     },
     zip_safe=False,
     distclass=BinaryDistribution,
     cmdclass={
         'install_headers': InstallHeaders,
         'install': InstallCommand,
     },
     # PyPI package information.
     classifiers=[
         'Development Status :: 5 - Production/Stable',
         'Intended Audience :: Developers',
         'Intended Audience :: Education',
         'Intended Audience :: Science/Research',
         'License :: OSI Approved :: Apache Software License',
         'Programming Language :: Python :: 2',
         'Programming Language :: Python :: 2.7',
         'Programming Language :: Python :: 3',
         'Programming Language :: Python :: 3.4',
         'Programming Language :: Python :: 3.5',
         'Programming Language :: Python :: 3.6',
         'Programming Language :: Python :: 3.7',
         'Topic :: Scientific/Engineering',
         'Topic :: Scientific/Engineering :: Mathematics',
         'Topic :: Scientific/Engineering :: Artificial Intelligence',
         'Topic :: Software Development',
         'Topic :: Software Development :: Libraries',
         'Topic :: Software Development :: Libraries :: Python Modules',
     ],
     license='Apache 2.0',
     keywords='tensorflow tensor machine learning',
 )
	# 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.
	# ==============================================================================
	"""TensorFlow is an open source machine learning framework for everyone.

	TensorFlow is an open source software library for high performance numerical
	computation. Its flexible architecture allows easy deployment of computation
	across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters
	of servers to mobile and edge devices.

	Originally developed by researchers and engineers from the Google Brain team
	within Google's AI organization, it comes with strong support for machine
	learning and deep learning and the flexible numerical computation core is used
	across many other scientific domains.
	"""

	from __future__ import absolute_import
	from __future__ import division
	from __future__ import print_function

	import fnmatch
	import os
	import re
	import sys

	from setuptools import Command
	from setuptools import find_packages
	from setuptools import setup
	from setuptools.command.install import install as InstallCommandBase
	from setuptools.dist import Distribution

	DOCLINES = __doc__.split('\n')

	# This version string is semver compatible, but incompatible with pip.
	# For pip, we will remove all '-' characters from this string, and use the
	# result for pip.
	# Also update tensorflow/tensorflow.bzl and
	# tensorflow/core/public/version.h
	_VERSION = '1.14.0'

	REQUIRED_PACKAGES = [
	'absl-py >= 0.7.0',
	'astor >= 0.6.0',
	'backports.weakref >= 1.0rc1;python_version<"3.4"',
	'enum34 >= 1.1.6;python_version<"3.4"',
	'gast == 0.2.2',
	'google_pasta >= 0.1.6',
	'keras_applications >= 1.0.8',
	'keras_preprocessing >= 1.0.5',
	'numpy >= 1.16.0, < 2.0',
	'opt_einsum >= 2.3.2',
	'six >= 1.10.0',
	'protobuf >= 3.6.1',
	'tensorboard >= 1.15.0, < 1.16.0',
	'tensorflow_estimator >= 1.14.0rc0, < 1.15.0rc0',
	'termcolor >= 1.1.0',
	'wrapt >= 1.11.1',
	# python3 requires wheel 0.26
	'wheel >= 0.26;python_version>="3"',
	'wheel;python_version<"3"',
	# mock comes with unittest.mock for python3, need to install for python2
	'mock >= 2.0.0;python_version<"3"',
	# functools comes with python3, need to install the backport for python2
	'functools32 >= 3.2.3;python_version<"3"',
	]

	if sys.byteorder == 'little':
	# grpcio does not build correctly on big-endian machines due to lack of
	# BoringSSL support.
	# See https://github.com/tensorflow/tensorflow/issues/17882.
	REQUIRED_PACKAGES.append('grpcio >= 1.8.6')

	project_name = 'tensorflow'
	if '--project_name' in sys.argv:
	project_name_idx = sys.argv.index('--project_name')
	project_name = sys.argv[project_name_idx + 1]
	sys.argv.remove('--project_name')
	sys.argv.pop(project_name_idx)

	# tf-nightly should depend on tb-nightly
	if 'tf_nightly' in project_name:
	for i, pkg in enumerate(REQUIRED_PACKAGES):
	if 'tensorboard' in pkg:
	REQUIRED_PACKAGES[i] = 'tb-nightly >= 2.0.0a0, < 2.1.0a0'
	elif 'tensorflow_estimator' in pkg and '2.0' in project_name:
	REQUIRED_PACKAGES[i] = 'tensorflow-estimator-2.0-preview'
	elif 'tensorflow_estimator' in pkg:
	REQUIRED_PACKAGES[i] = 'tf-estimator-nightly'

	# pylint: disable=line-too-long
	CONSOLE_SCRIPTS = [
	'toco_from_protos = tensorflow.lite.toco.python.toco_from_protos:main',
	'tflite_convert = tensorflow.lite.python.tflite_convert:main',
	'toco = tensorflow.lite.python.tflite_convert:main',
	'saved_model_cli = tensorflow.python.tools.saved_model_cli:main',
	# We need to keep the TensorBoard command, even though the console script
	# is now declared by the tensorboard pip package. If we remove the
	# TensorBoard command, pip will inappropriately remove it during install,
	# even though the command is not removed, just moved to a different wheel.
	'tensorboard = tensorboard.main:run_main',
	'tf_upgrade_v2 = tensorflow.tools.compatibility.tf_upgrade_v2_main:main',
	'estimator_ckpt_converter = tensorflow_estimator.python.estimator.tools.checkpoint_converter:main',
	]
	# pylint: enable=line-too-long

	# Only keep freeze_graph console script in 1.X.
	if _VERSION.startswith('1.') and '_2.0' not in project_name:
	CONSOLE_SCRIPTS.append(
	'freeze_graph = tensorflow.python.tools.freeze_graph:run_main')

	# remove the tensorboard console script if building tf_nightly
	if 'tf_nightly' in project_name:
	CONSOLE_SCRIPTS.remove('tensorboard = tensorboard.main:run_main')

	TEST_PACKAGES = [
	'scipy >= 0.15.1',
	]


	class BinaryDistribution(Distribution):

	def has_ext_modules(self):
	return True


	class InstallCommand(InstallCommandBase):
	"""Override the dir where the headers go."""

	def finalize_options(self):
	ret = InstallCommandBase.finalize_options(self)
	self.install_headers = os.path.join(self.install_purelib, 'tensorflow_core',
	'include')
	self.install_lib = self.install_platlib
	return ret


	class InstallHeaders(Command):
	"""Override how headers are copied.

	The install_headers that comes with setuptools copies all files to
	the same directory. But we need the files to be in a specific directory
	hierarchy for -I <include_dir> to work correctly.
	"""
	description = 'install C/C++ header files'

	user_options = [('install-dir=', 'd',
	'directory to install header files to'),
	('force', 'f',
	'force installation (overwrite existing files)'),
	]

	boolean_options = ['force']

	def initialize_options(self):
	self.install_dir = None
	self.force = 0
	self.outfiles = []

	def finalize_options(self):
	self.set_undefined_options('install',
	('install_headers', 'install_dir'),
	('force', 'force'))

	def mkdir_and_copy_file(self, header):
	install_dir = os.path.join(self.install_dir, os.path.dirname(header))
	# Get rid of some extra intervening directories so we can have fewer
	# directories for -I
	install_dir = re.sub('/google/protobuf_archive/src', '', install_dir)
	install_dir = re.sub('/include/tensorflow_core/', '/include/tensorflow/',
	install_dir)

	# Copy external code headers into tensorflow_core/include.
	# A symlink would do, but the wheel file that gets created ignores
	# symlink within the directory hierarchy.
	# NOTE(keveman): Figure out how to customize bdist_wheel package so
	# we can do the symlink.
	external_header_locations = [
	'tensorflow_core/include/external/eigen_archive/',
	'tensorflow_core/include/external/com_google_absl/',
	]
	for location in external_header_locations:
	if location in install_dir:
	extra_dir = install_dir.replace(location, '')
	if not os.path.exists(extra_dir):
	self.mkpath(extra_dir)
	self.copy_file(header, extra_dir)

	if not os.path.exists(install_dir):
	self.mkpath(install_dir)
	return self.copy_file(header, install_dir)

	def run(self):
	hdrs = self.distribution.headers
	if not hdrs:
	return

	self.mkpath(self.install_dir)
	for header in hdrs:
	(out, _) = self.mkdir_and_copy_file(header)
	self.outfiles.append(out)

	def get_inputs(self):
	return self.distribution.headers or []

	def get_outputs(self):
	return self.outfiles


	def find_files(pattern, root):
	"""Return all the files matching pattern below root dir."""
	for dirpath, _, files in os.walk(root):
	for filename in fnmatch.filter(files, pattern):
	yield os.path.join(dirpath, filename)


	so_lib_paths = [
	i for i in os.listdir('.')
	if os.path.isdir(i) and fnmatch.fnmatch(i, '_solib_*')
	]

	matches = []
	for path in so_lib_paths:
	matches.extend(
	['../' + x for x in find_files('*', path) if '.py' not in x]
	)

	if os.name == 'nt':
	EXTENSION_NAME = 'python/_pywrap_tensorflow_internal.pyd'
	else:
	EXTENSION_NAME = 'python/_pywrap_tensorflow_internal.so'

	headers = (
	list(find_files('*.h', 'tensorflow_core/core')) +
	list(find_files('*.h', 'tensorflow_core/stream_executor')) +
	list(find_files('*.h', 'google/com_google_protobuf/src')) +
	list(find_files('*.inc', 'google/com_google_protobuf/src')) +
	list(find_files('*', 'third_party/eigen3')) + list(
	find_files('*.h', 'tensorflow_core/include/external/com_google_absl')) +
	list(
	find_files('*.inc', 'tensorflow_core/include/external/com_google_absl'))
	+ list(find_files('*', 'tensorflow_core/include/external/eigen_archive')))

	setup(
	name=project_name,
	version=_VERSION.replace('-', ''),
	description=DOCLINES[0],
	long_description='\n'.join(DOCLINES[2:]),
	url='https://www.tensorflow.org/',
	download_url='https://github.com/tensorflow/tensorflow/tags',
	author='Google Inc.',
	author_email='packages@tensorflow.org',
	# Contained modules and scripts.
	packages=find_packages(),
	entry_points={
	'console_scripts': CONSOLE_SCRIPTS,
	},
	headers=headers,
	install_requires=REQUIRED_PACKAGES,
	tests_require=REQUIRED_PACKAGES + TEST_PACKAGES,
	# Add in any packaged data.
	include_package_data=True,
	package_data={
	'tensorflow': [
	EXTENSION_NAME,
	] + matches,
	},
	zip_safe=False,
	distclass=BinaryDistribution,
	cmdclass={
	'install_headers': InstallHeaders,
	'install': InstallCommand,
	},
	# PyPI package information.
	classifiers=[
	'Development Status :: 5 - Production/Stable',
	'Intended Audience :: Developers',
	'Intended Audience :: Education',
	'Intended Audience :: Science/Research',
	'License :: OSI Approved :: Apache Software License',
	'Programming Language :: Python :: 2',
	'Programming Language :: Python :: 2.7',
	'Programming Language :: Python :: 3',
	'Programming Language :: Python :: 3.4',
	'Programming Language :: Python :: 3.5',
	'Programming Language :: Python :: 3.6',
	'Programming Language :: Python :: 3.7',
	'Topic :: Scientific/Engineering',
	'Topic :: Scientific/Engineering :: Mathematics',
	'Topic :: Scientific/Engineering :: Artificial Intelligence',
	'Topic :: Software Development',
	'Topic :: Software Development :: Libraries',
	'Topic :: Software Development :: Libraries :: Python Modules',
	],
	license='Apache 2.0',
	keywords='tensorflow tensor machine learning',
	)