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setup.py
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setup.py
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# coding=utf-8
# Copyright 2018 The Gin-Config Authors.
#
# 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.
"""Setup script for gin-config.
See https://github.com/google/gin-config for documentation.
"""
from os import path
from setuptools import find_packages
from setuptools import setup
_VERSION = '0.4.0'
here = path.abspath(path.dirname(__file__))
long_description = """
# Gin
Gin provides a lightweight configuration framework for Python, based on
dependency injection. Functions or classes can be decorated with
`@gin.configurable`, allowing default parameter values to be supplied from a
config file (or passed via the command line) using a simple but powerful syntax.
This removes the need to define and maintain configuration objects (e.g.
protos), or write boilerplate parameter plumbing and factory code, while often
dramatically expanding a project's flexibility and configurability.
Gin is particularly well suited for machine learning experiments (e.g. using
TensorFlow), which tend to have many parameters, often nested in complex ways.
**Authors**: Dan Holtmann-Rice, Sergio Guadarrama, Nathan Silberman
**Contributors**: Oscar Ramirez, Marek Fiser
"""
install_requires = ['six >= 1.10.0']
setup(
name='gin-config',
version=_VERSION,
include_package_data=True,
packages=find_packages(exclude=['docs']), # Required
package_data={'testdata': ['testdata/*.gin']},
install_requires=install_requires,
extras_require={ # Optional
':python_version<"3"': ['enum34'],
'tensorflow': ['tensorflow >= 1.13.0'],
'tensorflow-gpu': ['tensorflow-gpu >= 1.13.0'],
'tf-nightly': ['tf-nightly'],
'torch': ['torch >= 1.3.0'],
'pytorch-nightly': ['pytorch-nightly'],
'testing': [
'six >= 1.10.0',
'absl-py >= 0.1.6',
'mock >= 3.0.5',
'nose',
]
},
description='Gin-Config: A lightweight configuration library for Python',
long_description=long_description,
long_description_content_type='text/markdown',
url='https://github.com/google/gin-config', # Optional
author='The Gin-Config Team', # Optional
classifiers=[ # Optional
'Development Status :: 3 - Alpha',
# Indicate who your project is intended for
'Intended Audience :: Developers',
'Intended Audience :: Education',
'Intended Audience :: Science/Research',
# Pick your license as you wish
'License :: OSI Approved :: Apache Software License',
# Specify the Python versions you support here. In particular, ensure
# that you indicate whether you support Python 2, Python 3 or both.
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'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',
],
project_urls={ # Optional
'Documentation': 'https://github.com/google/gin-config/docs',
'Bug Reports': 'https://github.com/google/gin-config/issues',
'Source': 'https://github.com/google/gin-config',
},
license='Apache 2.0',
keywords='gin-config gin python configuration machine learning'
)