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setup.py
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setup.py
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import setuptools
import sys
if sys.version_info < (3, 7):
raise ValueError(
'Auto-Pytorch requires Python 3.7 or higher, but found version {}.{}.{}'.format(
sys.version_info.major, sys.version_info.minor, sys.version_info.micro
)
)
with open("README.md", "r") as f:
long_description = f.read()
requirements = []
with open("requirements.txt", "r") as f:
for line in f:
requirements.append(line.strip())
# noinspection PyInterpreter
setuptools.setup(
name="autoPyTorch",
version="0.2.1",
author="AutoML Freiburg",
author_email="eddiebergmanhs@gmail.com",
description=("Auto-PyTorch searches neural architectures using smac"),
long_description=long_description,
url="https://github.com/automl/Auto-PyTorch",
long_description_content_type="text/markdown",
license="3-clause BSD",
keywords="machine learning algorithm configuration hyperparameter"
"optimization tuning neural architecture deep learning",
packages=setuptools.find_packages(),
package_data={"autoPyTorch": ['py.typed']},
classifiers=[
"Development Status :: 3 - Alpha",
"Topic :: Utilities",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
"License :: OSI Approved :: BSD License",
],
python_requires='>=3.7',
platforms=['Linux'],
install_requires=requirements,
include_package_data=True,
extras_require={
"forecasting": [
"gluonts>=0.10.0",
"sktime",
"pytorch-forecasting",
],
"test": [
"matplotlib",
"pytest",
"pytest-xdist",
"pytest-timeout",
"flaky",
"pyarrow",
"pre-commit",
"pytest-cov",
'pytest-forked',
'pytest-subtests',
"codecov",
"pep8",
"mypy",
"openml",
"emcee",
"scikit-optimize",
"pyDOE",
],
"examples": [
"matplotlib",
"jupyter",
"notebook",
"seaborn",
"openml"
],
"docs": ["sphinx", "sphinx-gallery", "sphinx_bootstrap_theme", "numpydoc"],
},
test_suite="pytest",
data_files=[('configs', ['autoPyTorch/configs/default_pipeline_options.json']),
('portfolio', ['autoPyTorch/configs/greedy_portfolio.json']),
('forecasting_init', ['autoPyTorch/configs/forecasting_init_cfgs.json'])],
dependency_links=['https://github.com/automl/automl_common.git/tarball/autoPyTorch#egg=package-0.0.1']
)