text: # lint as: python3
  # 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.
  
  [![Python](https://img.shields.io/pypi/pyversions/tensorflow.svg?style=plastic)](https://badge.fury.io/py/tensorflow)
  [![PyPI](https://badge.fury.io/py/tensorflow.svg)](https://badge.fury.io/py/tensorflow)
  
  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.
  """
  
  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
  
  
  # 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 = '2.8.0'
  
  
  # We use the same setup.py for all tensorflow_* packages and for the nightly
  # equivalents (tf_nightly_*). The package is controlled from the argument line
  # when building the pip package.
  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)
  
  
  # All versions of TF need these packages. We indicate the widest possible range
  # of package releases possible to be as up-to-date as possible as well as to
  # accomodate as many pre-installed packages as possible.
  # For packages that don't have yet a stable release, we pin using `~= 0.x` which
  # means we accept any `0.y` version (y >= x) but not the first major release. We
  # will need additional testing for that.
  # NOTE: This assumes that all packages follow SemVer. If a package follows a
  # different versioning scheme (e.g., PVP), we use different bound specifier and
  # comment the versioning scheme.
  # NOTE: Please add test only packages to `TEST_PACKAGES` below.
  REQUIRED_PACKAGES = [
      # NOTE: As numpy has releases that break semver guarantees and several other
      # deps depend on numpy without an upper bound, we must install numpy before
      # everything else.
      'numpy >= 1.14.5', # keras 2.6 needs 1.19.2, h5py needs 1.14.5 for py37
      # Install other dependencies
      'absl-py >= 0.4.0',
      'astunparse >= 1.6.0',
      'libclang >= 9.0.1',
      'flatbuffers >= 1.12, < 3.0', # capped as jax 0.1.71 needs < 3.0
      'google_pasta >= 0.1.1',
      'h5py >= 2.9.0', # capped since 3.3.0 lacks py3.6
      'keras_preprocessing >= 1.1.1', # 1.1.0 needs tensorflow==1.7
      'opt_einsum >= 2.3.2', # sphinx pin not removed up til 3.3.0 release
      'protobuf >= 3.9.2',
      'six >= 1.12.0',
      'termcolor >= 1.1.0',
      'typing_extensions >= 3.6.6',
      'wheel >= 0.32.0, < 1.0', # capped as astunparse 1.6.0-1.6.3 requires < 1.0
      'wrapt >= 1.11.0',
      # These packages need to be pinned exactly as newer versions are
      # incompatible with the rest of the ecosystem
      'gast >= 0.2.1, < 0.5.0', # TODO(lpak): if this breaks, revert to 0.4.0
      # TensorFlow ecosystem packages that TF exposes API for
      # These need to be in sync with the existing TF version
      # They are updated during the release process
      # When updating these, please also update the nightly versions below
      'tensorboard ~= 2.6',
      'tensorflow_estimator >= 2.7.0, < 2.8',
      # Keras release is not backward compatible with old tf release, and we have
      # to make the version aligned between TF and Keras.
      'keras >= 2.7.0, < 2.8',
      'tensorflow-io-gcs-filesystem >= 0.21.0',
  ]
  
  
  # For nightly packages, instead of depending on tensorboard,
  # tensorflow_estimator and keras, we depend on their nightly equivalent.
  # When updating these, make sure to also update the release versions above.
  # NOTE: the nightly versions are one version ahead of the release ones!
  # NOTE: the nightly versions specify alpha/dev!
  if 'tf_nightly' in project_name:
    for i, pkg in enumerate(REQUIRED_PACKAGES):
      if 'tensorboard' in pkg:
        REQUIRED_PACKAGES[i] = 'tb-nightly ~= 2.7.0.a'
      elif 'tensorflow_estimator' in pkg:
        REQUIRED_PACKAGES[i] = 'tf-estimator-nightly ~= 2.8.0.dev'
      elif 'keras' in pkg and 'keras_preprocessing' not in pkg:
        REQUIRED_PACKAGES[i] = 'keras-nightly ~= 2.8.0.dev'
  
  
  # grpcio does not build correctly on big-endian machines due to lack of
  # BoringSSL support.
  # See https://github.com/tensorflow/tensorflow/issues/17882.
  if sys.byteorder == 'little':
    REQUIRED_PACKAGES.append('grpcio >= 1.24.3, < 2.0')
  
  
  # Packages which are only needed for testing code.
  # Please don't add test-only packages to `REQUIRED_PACKAGES`!
  # Follows the same conventions as `REQUIRED_PACKAGES`
  TEST_PACKAGES = [
      'portpicker >= 1.3.1',
      'scipy ~= 1.5.2, < 1.7', # NOTE: capped due to py3.6 and opt-einsum requires
      # sphinx==1.2.3 but scipy 1.7.1 requires sphinx >= 2.4.0, <3.1.0
      'tblib >= 1.4.0',
      'dill >= 0.2.9',
  ]
  
  
  DOCLINES = __doc__.split('\n')
  if project_name.endswith('-gpu'):
    project_name_no_gpu = project_name[:-len('-gpu')]
    _GPU_PACKAGE_NOTE = 'Note that %s package by default supports both CPU and '\
        'GPU. %s has the same content and exists solely for backward '\
        'compatibility. Please migrate to %s for GPU support.'\
        % (project_name_no_gpu, project_name, project_name_no_gpu)
    DOCLINES.append(_GPU_PACKAGE_NOTE)
  
  
  # 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',
      'import_pb_to_tensorboard = tensorflow.python.tools.import_pb_to_tensorboard: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
  
  # remove the tensorboard console script if building tf_nightly
  if 'tf_nightly' in project_name:
    CONSOLE_SCRIPTS.remove('tensorboard = tensorboard.main:run_main')
  
  
  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)  # pylint: disable=assignment-from-no-return
      self.install_headers = os.path.join(self.install_platlib, 'tensorflow',
                                          '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)
  
      # Copy external code headers into tensorflow/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/include/external/eigen_archive/',
          'tensorflow/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('*.proto', 'tensorflow/compiler')) +
      list(find_files('*.proto', 'tensorflow/core')) +
      list(find_files('*.proto', 'tensorflow/python')) +
      list(find_files('*.proto', 'tensorflow/python/framework')) +
      list(find_files('*.def', 'tensorflow/compiler')) +
      list(find_files('*.h', 'tensorflow/c')) +
      list(find_files('*.h', 'tensorflow/cc')) +
      list(find_files('*.h', 'tensorflow/compiler')) +
      list(find_files('*.h.inc', 'tensorflow/compiler')) +
      list(find_files('*.h', 'tensorflow/core')) +
      list(find_files('*.h', 'tensorflow/lite/kernels/shim')) +
      list(find_files('*.h', 'tensorflow/python')) +
      list(find_files('*.h', 'tensorflow/python/client')) +
      list(find_files('*.h', 'tensorflow/python/framework')) +
      list(find_files('*.h', 'tensorflow/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/include/external/com_google_absl')) +
      list(find_files('*.inc', 'tensorflow/include/external/com_google_absl')) +
      list(find_files('*', 'tensorflow/include/external/eigen_archive')))
  
  setup(
      name=project_name,
      version=_VERSION.replace('-', ''),
      description=DOCLINES[0],
      long_description='\n'.join(DOCLINES[2:]),
      long_description_content_type="text/markdown",
      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=sorted([
          'Development Status :: 5 - Production/Stable',
          # TODO(angerson) Add IFTTT when possible
          'Environment :: GPU :: NVIDIA CUDA :: 11.2',
          'Intended Audience :: Developers',
          'Intended Audience :: Education',
          'Intended Audience :: Science/Research',
          'License :: OSI Approved :: Apache Software License',
          'Programming Language :: Python :: 3',
          'Programming Language :: Python :: 3.7',
          'Programming Language :: Python :: 3.8',
          'Programming Language :: Python :: 3.9',
          'Programming Language :: Python :: 3 :: Only',
          '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',
  )
  