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setup.py
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setup.py
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#from distutils.core import setup
from setuptools import setup
from setuptools import Extension
from Cython.Build import cythonize
from codecs import open
from os import path
import numpy as np
VERSION = '2016.11'
# Get the long description from the relevant file
with open(path.join('README.rst'), encoding='utf-8') as f:
LONG_DESCRIPTION = f.read()
blas_info = np.__config__.get_info('blas_opt_info')
setup(
name='binet',
version=VERSION,
description='Deep Neural Net code for GPUs and CPUs',
long_description=LONG_DESCRIPTION,
url='https://github.com/bioinf-jku/binet',
# Author details
author='Thomas Unterthiner',
author_email='thomas.unterthiner@gmx.net',
# Choose your license
license='GPLv2+',
# See https://pypi.python.org/pypi?%3Aaction=list_classifiers
classifiers=['Development Status :: 4 - Beta',
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering',
'Topic :: Software Development',
'License :: OSI Approved :: GNU General Public License v2 or later (GPLv2+)',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.6',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.3',
'Programming Language :: Python :: 3.4',
],
keywords='Machine Learning Deep Learning Neural Nets',
# You can just specify the packages manually here if your project is
# simple. Or you can use find_packages().
packages=['binet'],
ext_modules = cythonize([Extension("binet.op", ["binet/op.pyx"],
libraries=blas_info.get('libraries', []),
extra_link_args=blas_info.get('extra_link_args', []),
extra_compile_args=blas_info.get('extra_compile_args', []) + ['-Wno-unused-function'],
define_macros=blas_info.get('define_macros', []),
library_dirs=blas_info.get('library_dirs', []),
include_dirs=[np.get_include()] + blas_info.get('include_dirs', []),
)
]),
setup_requires=["cffi>=1.0.0"],
cffi_modules=["binet/external_build.py:ffi"],
install_requires=['cffi>=1.0.0', 'numpy', 'scikit-learn'],
)