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setup.py
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setup.py
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# Sebastian Raschka 2020
# coral_pytorch
# Author: Sebastian Raschka <sebastianraschka.com>
#
# License: MIT
from os.path import realpath, dirname, join
from setuptools import setup, find_packages
import coral_pytorch
VERSION = coral_pytorch.__version__
PROJECT_ROOT = dirname(realpath(__file__))
REQUIREMENTS_FILE = join(PROJECT_ROOT, 'requirements.txt')
with open(REQUIREMENTS_FILE) as f:
install_reqs = f.read().splitlines()
install_reqs.append('setuptools')
setup(name='coral_pytorch',
version=VERSION,
description='CORAL ordinal regression for PyTorch',
author='Sebastian Raschka',
author_email='mail@sebastianraschka.com',
url='https://github.com/raschka-research-group/coral_pytorch',
packages=find_packages(),
package_data={'': ['LICENSE.txt',
'README.md',
'requirements.txt']
},
include_package_data=True,
setup_requires=[],
install_requires=install_reqs,
extras_require={'testing': ['pytest'],
'docs': ['mkdocs']},
license='MIT',
platforms='any',
keywords=['deep learning', 'pytorch', 'AI'],
classifiers=[
'License :: OSI Approved :: MIT License',
'Development Status :: 5 - Production/Stable',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX',
'Operating System :: Unix',
'Operating System :: MacOS',
'Programming Language :: Python :: 3.7',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Scientific/Engineering :: Information Analysis',
'Topic :: Scientific/Engineering :: Image Recognition',
],
long_description_content_type='text/markdown',
long_description="""
Library implementing the core utilities for the
CORAL ordinal regression approach from
Wenzhi Cao, Vahid Mirjalili, Sebastian Raschka (2020):
Rank Consistent Ordinal Regression for Neural Networks
with Application to Age Estimation.
Pattern Recognition Letters.
https://doi.org/10.1016/j.patrec.2020.11.008.
""")