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setup.py
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setup.py
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import setuptools
version = "0.2.1"
with open("aix360/version.py", "w") as f:
f.write('# generated by setup.py\nversion = "{}"\n'.format(version))
extra_requires = {
"default": [
"numpy",
"pandas",
"scikit-learn",
"matplotlib",
],
"rbm": [
"matplotlib",
"pandas<=1.4.3",
"scipy>=0.17",
"scikit-learn<1.2.0",
"cvxpy>=1.1",
],
"profwt": [
"keras==2.3.1",
"scipy>=0.17",
"tensorflow==1.14",
],
"cofrnet": [
"pandas<=1.4.3",
"torch",
"tqdm",
],
"ted": [
"pandas",
"scikit-learn",
],
"dipvae": [
"matplotlib",
"torch",
"torchvision",
],
"rule_induction": [
"matplotlib",
"numba",
"pandas<=1.4.3",
"scikit-learn",
"nyoka",
"cvxpy",
"xmltodict==0.12.0",
],
"lime": [
"lime",
"tqdm",
"pandas",
],
"matching": ["otoc @ git+https://github.com/IBM/otoc@main#egg=otoc"],
"protodash": [
"scikit-learn",
"xport",
"cvxpy",
"requests",
],
"contrastive": [
"keras==2.3.1",
"tensorflow==1.14",
"requests",
"scipy>=0.17",
"scikit-image",
"torch",
"h5py<3.0.0", # to resolve keras error: 'str' object has no attribute 'decode'
],
"shap": [
"keras==2.3.1",
"tensorflow==1.14",
"matplotlib",
"numba",
"pandas<=1.4.3",
"shap",
"tqdm",
],
"nncontrastive": [
"pandas<=1.4.3",
"tensorflow==2.9.3",
],
}
# minimal dependencies in install_requires
install_requires = extra_requires["default"] # ted is supported by default.
setuptools.setup(
name="aix360",
version=version,
description="IBM AI Explainability 360",
authos="aix360 developers",
url="https://github.com/IBM/AIX360",
author_email="aix360@us.ibm.com",
packages=setuptools.find_packages(),
license="Apache License 2.0",
long_description=open("README.md", "r", encoding="utf-8").read(),
long_description_content_type="text/markdown",
install_requires=install_requires,
extras_require=extra_requires,
package_data={
"aix360": [
"data/*",
"data/*/*",
"data/*/*/*",
"models/*",
"models/*/*",
"models/*/*/*",
]
},
include_package_data=True,
zip_safe=False,
)