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setup.py
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from setuptools import setup
install_requires = [
'numpy >= 1.13.0',
'torchvision >= 0.2.0',
'scikit-learn >= 0.18.0',
'scipy >= 1.0.0',
'pandas >= 0.21.0',
'torch >= 0.4.0',
'numba >= 0.37.0',
'psutil >= 4.0.0'
]
dependency_links = [
]
desc = """\
HyperLearn
Faster, Leaner Scikit Learn (Sklearn) morphed with Statsmodels &
Deep Learning drop in substitute. Designed for big data, HyperLearn
can use 50%+ less memory, and runs 50%+ faster on some modules.
Will have GPU support, and all modules are parallelized.
Written completely in PyTorch, Numba, Numpy, Pandas, Scipy & LAPACK.
https://github.com/danielhanchen/hyperlearn
"""
setup(name = 'hyperlearn',
version = '0.0.1',
author = 'Daniel Han-Chen & Others listed on Github',
url = 'https://github.com/danielhanchen/hyperlearn',
long_description = desc,
py_modules = ['hyperlearn'],
install_requires = install_requires,
dependency_links = dependency_links,
classifiers=[ # Optional
'Development Status :: 1 - Planning',
# 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 :: GNU General Public License v3 (GPLv3)',
# 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 :: 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',
]
)