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setup.py
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61 lines (55 loc) · 2.28 KB
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import versioneer
from setuptools import find_packages, setup
DISTNAME = "mygrad"
LICENSE = "MIT"
AUTHOR = "Ryan Soklaski"
AUTHOR_EMAIL = "rsoklaski@gmail.com"
URL = "https://github.com/rsokl/MyGrad"
CLASSIFIERS = [
"Development Status :: 5 - Production/Stable",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
"Intended Audience :: Science/Research",
"Intended Audience :: Education",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Topic :: Scientific/Engineering",
]
INSTALL_REQUIRES = ["numpy >= 1.17"]
TESTS_REQUIRE = ["pytest >= 3.8", "hypothesis >= 5.32.0", "scipy"]
DESCRIPTION = "A sleek auto-differentiation library that wraps numpy."
LONG_DESCRIPTION = """
mygrad is a simple, NumPy-centric autograd library. An autograd library enables
you to automatically compute derivatives of mathematical functions. This library is
designed to serve primarily as an education tool for learning about gradient-based
machine learning; it is easy to install, has a readable and easily customizable code base,
and provides a sleek interface that mimics NumPy. Furthermore, it leverages NumPy's
vectorization to achieve good performance despite the library's simplicity.
This is not meant to be a competitor to libraries like PyTorch (which mygrad most
closely resembles) or TensorFlow. Rather, it is meant to serve as a useful tool for
students who are learning about training neural networks using back propagation.
"""
setup(
name=DISTNAME,
version=versioneer.get_version(),
cmdclass=versioneer.get_cmdclass(),
license=LICENSE,
author=AUTHOR,
author_email=AUTHOR_EMAIL,
classifiers=CLASSIFIERS,
description=DESCRIPTION,
long_description=LONG_DESCRIPTION,
install_requires=INSTALL_REQUIRES,
tests_require=TESTS_REQUIRE,
extras_require={
"rnn": ["numba>=0.34.0"] # GRU and vanilla RNN require numba-acceleration
},
url=URL,
download_url="https://github.com/rsokl/mygrad/tarball/" + versioneer.get_version(),
python_requires=">=3.7",
packages=find_packages(where="src", exclude=["tests", "tests.*"]),
package_dir={"": "src"},
)