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setup.py
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setup.py
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# Copyright 2019 Google LLC. 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.
"""Package Setup script for TFX."""
import logging
import os
import shutil
import subprocess
import sys
import setuptools
from setuptools import find_namespace_packages
from setuptools import setup
from setuptools.command import develop
# pylint: disable=g-bad-import-order
# It is recommended to import setuptools prior to importing distutils to avoid
# using legacy behavior from distutils.
# https://setuptools.readthedocs.io/en/latest/history.html#v48-0-0
from distutils.command import build
# pylint: enable=g-bad-import-order
from tfx import dependencies
from tfx import version
from wheel import bdist_wheel
# Prefer to import `package_config` from the setup.py script's directory. The
# `package_config.py` file is used to configure which package to build (see
# the logic below switching on `package_config.PACKAGE_NAME`) and the overall
# package build README at `package_build/README.md`.
sys.path.insert(0, os.path.dirname(__file__))
# pylint: disable=g-bad-import-order,g-import-not-at-top
import package_config
# pylint: enable=g-bad-import-order,g-import-not-at-top
class _BdistWheelCommand(bdist_wheel.bdist_wheel):
"""Overrided bdist_wheel command.
Inject some custom command line arguments and flags that can be used in the
subcommands. This command class covers:
- pip wheel --build-option="--local-mlmd-repo=${MLMD_OUTPUT_DIR}"
- python setup.py bdist_wheel --local-mlmd-repo="${MLMD_OUTPUT_DIR}"
"""
user_options = bdist_wheel.bdist_wheel.user_options + [
('local-mlmd-repo=', None, 'Path to the local MLMD repository to use '
'instead of the Bazel com_github_google_ml_metadata remote repository.')
]
def initialize_options(self):
# Run super().initialize_options. Command is an old-style class (i.e.
# doesn't inherit object) and super() fails in python 2.
bdist_wheel.bdist_wheel.initialize_options(self)
self.local_mlmd_repo = None
def finalize_options(self):
bdist_wheel.bdist_wheel.finalize_options(self)
gen_proto = self.distribution.get_command_obj('gen_proto')
gen_proto.local_mlmd_repo = self.local_mlmd_repo
class _UnsupportedDevBuildWheelCommand(_BdistWheelCommand):
"""Disables build of 'tfx-dev' wheel files."""
def finalize_options(self):
if not os.environ.get('UNSUPPORTED_BUILD_TFX_DEV_WHEEL'):
raise Exception(
'Starting in version 0.26.0, pip package build for TFX has changed,'
'and `python setup.py bdist_wheel` can no longer be invoked '
'directly.\n\nFor instructions on how to build wheels for TFX, see '
'https://github.com/tensorflow/tfx/blob/master/package_build/'
'README.md.\n\nEditable pip installation for development is still '
'supported through `pip install -e`.')
super().finalize_options()
class _BuildCommand(build.build):
"""Build everything that is needed to install.
This overrides the original distutils "build" command to to run gen_proto
command before any sub_commands.
build command is also invoked from bdist_wheel and install command, therefore
this implementation covers the following commands:
- pip install . (which invokes bdist_wheel)
- python setup.py install (which invokes install command)
- python setup.py bdist_wheel (which invokes bdist_wheel command)
"""
def _should_generate_proto(self):
"""Predicate method for running GenProto command or not."""
return True
# Add "gen_proto" command as the first sub_command of "build". Each
# sub_command of "build" (e.g. "build_py", "build_ext", etc.) is executed
# sequentially when running a "build" command, if the second item in the tuple
# (predicate method) is evaluated to true.
sub_commands = [
('gen_proto', _should_generate_proto),
] + build.build.sub_commands
class _DevelopCommand(develop.develop):
"""Developmental install.
https://setuptools.readthedocs.io/en/latest/setuptools.html#development-mode
Unlike normal package installation where distribution is copied to the
site-packages folder, developmental install creates a symbolic link to the
source code directory, so that your local code change is immediately visible
in runtime without re-installation.
This is a setuptools-only (i.e. not included in distutils) command that is
also used in pip's editable install (pip install -e). Originally it only
invokes build_py and install_lib command, but we override it to run gen_proto
command in advance.
This implementation covers the following commands:
- pip install -e . (developmental install)
- python setup.py develop (which is invoked from developmental install)
"""
def run(self):
self.run_command('gen_proto')
# Run super().initialize_options. Command is an old-style class (i.e.
# doesn't inherit object) and super() fails in python 2.
develop.develop.run(self)
class _GenProtoCommand(setuptools.Command):
"""Generate proto stub files in python.
Running this command will populate foo_pb2.py file next to your foo.proto
file.
"""
user_options = [
('local-mlmd-repo=', None, 'Path to the local MLMD repository to use '
'instead of the Bazel com_github_google_ml_metadata remote repository.')
]
def initialize_options(self):
self.local_mlmd_repo = None
def finalize_options(self):
self._bazel_cmd = shutil.which('bazel')
if not self._bazel_cmd:
raise RuntimeError(
'Could not find "bazel" binary. Please visit '
'https://docs.bazel.build/versions/master/install.html for '
'installation instruction.')
def run(self):
bazel_args = ['--compilation_mode', 'opt']
if self.local_mlmd_repo:
# If local MLMD repo is given, override com_github_google_ml_metadata
# remote repository with the local path. This is required to use the
# local developmental version of MLMD during tests.
# https://docs.bazel.build/versions/master/command-line-reference.html
bazel_args.append('--override_repository={}={}'.format(
'com_github_google_ml_metadata', self.local_mlmd_repo))
cmd = [self._bazel_cmd, 'run', *bazel_args, '//build:gen_proto']
print('Running Bazel command', cmd, file=sys.stderr)
subprocess.check_call(
cmd,
# Bazel should be invoked in a directory containing bazel WORKSPACE
# file, which is the root directory.
cwd=os.path.dirname(os.path.realpath(__file__)),
env=os.environ)
_TFX_DESCRIPTION = (
'TensorFlow Extended (TFX) is a TensorFlow-based general-purpose machine '
'learning platform implemented at Google.')
_PIPELINES_SDK_DESCRIPTION = (
'A dependency-light distribution of the core pipeline authoring '
'functionality of TensorFlow Extended (TFX).')
# Get the long descriptions from README files.
with open('README.md') as fp:
_TFX_LONG_DESCRIPTION = fp.read()
with open('README.ml-pipelines-sdk.md') as fp:
_PIPELINES_SDK_LONG_DESCRIPTION = fp.read()
package_name = package_config.PACKAGE_NAME
tfx_extras_requires = {
# In order to use 'docker-image' or 'all', system libraries specified
# under 'tfx/tools/docker/Dockerfile' are required
'docker-image': dependencies.make_extra_packages_docker_image(),
'airflow': dependencies.make_extra_packages_airflow(),
'flax': dependencies.make_extra_packages_flax(),
'kfp': dependencies.make_extra_packages_kfp(),
'tfjs': dependencies.make_extra_packages_tfjs(),
'tf-ranking': dependencies.make_extra_packages_tf_ranking(),
'tfdf': dependencies.make_extra_packages_tfdf(),
'tflite-support': dependencies.make_extra_packages_tflite_support(),
'examples': dependencies.make_extra_packages_examples(),
'test': dependencies.make_extra_packages_test(),
'all': dependencies.make_extra_packages_all(),
}
# Packages included the TFX namespace.
TFX_NAMESPACE_PACKAGES = [
'tfx', 'tfx.*', 'tfx.orchestration', 'tfx.orchestration.*'
]
# Packages within the TFX namespace that are to be included in the base
# "ml-pipelines-sdk" pip package (and excluded from the "tfx" pip package,
# which takes "ml-pipelines-sdk" as a dependency).
ML_PIPELINES_SDK_PACKAGES = [
# This adds `tfx.version` which is needed in several places.
'tfx',
# Core DSL subpackage.
'tfx.dsl',
'tfx.dsl.*',
# The "ml-pipelines-sdk" package currently only supports local execution.
# These are the subpackages of `tfx.orchestration` necessary.
'tfx.orchestration',
'tfx.orchestration.config',
'tfx.orchestration.experimental.core',
'tfx.orchestration.launcher',
'tfx.orchestration.local',
'tfx.orchestration.local.legacy',
'tfx.orchestration.portable',
'tfx.orchestration.portable.*',
# Note that `tfx.proto` contains TFX first-party component-specific
# protobuf definitions, but `tfx.proto.orchestration` contains portable
# execution protobuf definitions which are needed in the base package.
'tfx.proto.orchestration',
# TODO(b/176814928): Consider moving relevant modules under
# `tfx.orchestration.*` to `tfx.dsl.*` as appropriate.
'tfx.proto.orchestration.*',
# TODO(b/176795329): Move `tfx.utils` to a location that emphasizes that
# these are internal utilities.
'tfx.utils',
'tfx.utils.*',
# TODO(b/176795331): Move `Artifact` and `ComponentSpec` classes into
# `tfx.dsl.*`.
'tfx.types',
'tfx.types.*',
]
EXCLUDED_PACKAGES = [
'tfx.benchmarks',
'tfx.benchmarks.*',
]
# Below console_scripts, each line identifies one console script. The first
# part before the equals sign (=) which is 'tfx', is the name of the script
# that should be generated, the second part is the import path followed by a
# colon (:) with the Click command group. After installation, the user can
# invoke the CLI using "tfx <command_group> <sub_command> <flags>"
TFX_ENTRY_POINTS = """
[console_scripts]
tfx=tfx.tools.cli.cli_main:cli_group
"""
ML_PIPELINES_SDK_ENTRY_POINTS = None
# This `setup.py` file can be used to build packages in 3 configurations. See
# the discussion in `package_build/README.md` for an overview. The `tfx` and
# `ml-pipelines-sdk` pip packages can be built for distribution using the
# selectable `package_config.PACKAGE_NAME` specifier. Additionally, for
# development convenience, the `tfx-dev` package containing the union of the
# the `tfx` and `ml-pipelines-sdk` package can be installed as an editable
# package using `pip install -e .`, but should not be built for distribution.
if package_config.PACKAGE_NAME == 'tfx-dev':
# Monolithic development package with the entirety of `tfx.*` and the full
# set of dependencies. Functionally equivalent to the union of the "tfx" and
# "tfx-pipeline-sdk" packages.
install_requires = dependencies.make_required_install_packages()
extras_require = tfx_extras_requires
description = _TFX_DESCRIPTION
long_description = _TFX_LONG_DESCRIPTION
packages = find_namespace_packages(
include=TFX_NAMESPACE_PACKAGES, exclude=EXCLUDED_PACKAGES)
# Do not support wheel builds for "tfx-dev".
build_wheel_command = _UnsupportedDevBuildWheelCommand # pylint: disable=invalid-name
# Include TFX entrypoints.
entry_points = TFX_ENTRY_POINTS
elif package_config.PACKAGE_NAME == 'ml-pipelines-sdk':
# Core TFX pipeline authoring SDK, without dependency on component-specific
# packages like "tensorflow" and "apache-beam".
install_requires = dependencies.make_pipeline_sdk_required_install_packages()
extras_require = {}
description = _PIPELINES_SDK_DESCRIPTION
long_description = _PIPELINES_SDK_LONG_DESCRIPTION
packages = find_namespace_packages(
include=ML_PIPELINES_SDK_PACKAGES, exclude=EXCLUDED_PACKAGES)
# Use the default pip wheel building command.
build_wheel_command = bdist_wheel.bdist_wheel # pylint: disable=invalid-name
# Include ML Pipelines SDK entrypoints.
entry_points = ML_PIPELINES_SDK_ENTRY_POINTS
elif package_config.PACKAGE_NAME == 'tfx':
# Recommended installation package for TFX. This package builds on top of
# the "ml-pipelines-sdk" pipeline authoring SDK package and adds first-party
# TFX components and additional functionality.
install_requires = (['ml-pipelines-sdk==%s' % version.__version__] +
dependencies.make_required_install_packages())
extras_require = tfx_extras_requires
description = _TFX_DESCRIPTION
long_description = _TFX_LONG_DESCRIPTION
packages = find_namespace_packages(
include=TFX_NAMESPACE_PACKAGES,
exclude=ML_PIPELINES_SDK_PACKAGES + EXCLUDED_PACKAGES)
# Use the pip wheel building command that includes proto generation.
build_wheel_command = _BdistWheelCommand # pylint: disable=invalid-name
# Include TFX entrypoints.
entry_points = TFX_ENTRY_POINTS
else:
raise ValueError('Invalid package config: %r.' % package_config.PACKAGE_NAME)
logging.info('Executing build for package %r.', package_name)
setup(
name=package_name,
version=version.__version__,
author='Google LLC',
author_email='[email protected]',
license='Apache 2.0',
classifiers=[
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Developers',
'Intended Audience :: Education',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: Apache Software License',
'Operating System :: OS Independent',
'Programming Language :: Python',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Programming Language :: Python :: 3 :: Only',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Scientific/Engineering :: Mathematics',
'Topic :: Software Development',
'Topic :: Software Development :: Libraries',
'Topic :: Software Development :: Libraries :: Python Modules',
],
namespace_packages=[],
install_requires=install_requires,
extras_require=extras_require,
# TODO(b/158761800): Move to [build-system] requires in pyproject.toml.
setup_requires=[
'pytest-runner',
],
cmdclass={
'bdist_wheel': build_wheel_command,
'build': _BuildCommand,
'develop': _DevelopCommand,
'gen_proto': _GenProtoCommand,
},
python_requires='>=3.9,<3.11',
packages=packages,
include_package_data=True,
description=description,
long_description=long_description,
long_description_content_type='text/markdown',
keywords='tensorflow tfx',
url='https://www.tensorflow.org/tfx',
download_url='https://github.com/tensorflow/tfx/tags',
requires=[],
entry_points=entry_points,
)