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setup.py
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setup.py
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from setuptools import find_packages, setup
import os
this = os.path.dirname(__file__)
packages = find_packages()
assert packages
# read version from the package file.
with (open(os.path.join(this, "hummingbird/__init__.py"), "r")) as f:
line = [_ for _ in [_.strip("\r\n ") for _ in f.readlines()] if _.startswith("__version__")]
if len(line) > 0:
version_str = line[0].split("=")[1].strip('" ')
README = os.path.join(os.getcwd(), "README.md")
with open(README) as f:
long_description = f.read()
start_pos = long_description.find("## Introduction")
if start_pos >= 0:
long_description = long_description[start_pos:]
install_requires = [
"numpy>=1.15",
"onnxconverter-common>=1.6.0",
"scipy",
"scikit-learn",
"torch>1.7.0",
"psutil",
"dill",
"protobuf>=3.20.0,<=3.20.1",
]
onnx_requires = [
"onnxruntime>=1.0.0",
"onnxmltools>=1.6.0,<=1.11.0",
"skl2onnx>=1.7.0,<=1.12.0",
]
extra_requires = [
# The need each for these depends on which libraries you plan to convert from
"xgboost>=0.90",
"lightgbm>=2.2",
"prophet==1.1",
]
setup(
name="hummingbird-ml",
version=version_str,
description="Convert trained traditional machine learning models into tensor computations",
long_description=long_description,
long_description_content_type="text/markdown",
license="MIT License",
author="Microsoft Corporation",
author_email="[email protected]",
url="https://github.com/microsoft/hummingbird",
packages=packages,
include_package_data=True,
install_requires=install_requires,
extras_require={
"tests": ["flake8", "pytest", "coverage", "pre-commit"],
"sparkml": ["pyspark>=2.4.4,<3.1.2", "pyarrow>1.0"],
"onnx": onnx_requires,
"extra": extra_requires,
"benchmark": onnx_requires + extra_requires + ["memory-profiler", "psutil"],
},
classifiers=[
"Environment :: Console",
"Intended Audience :: Developers",
"Programming Language :: Python",
"Operating System :: OS Independent",
"License :: OSI Approved :: MIT License",
],
python_requires=">=3.8",
)