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import codecs
import os
from setuptools import find_packages, setup
with open("README.md", "r") as fh:
long_description = fh.read()
install_requires = [
"numpy>=1.18.0",
"scipy>=1.4.1",
"scikit-learn>=0.22.2",
"six",
"setuptools",
"tqdm",
]
docs_require = [
"sphinx >= 1.4",
"sphinx_rtd_theme",
"sphinx-autodoc-annotation",
"sphinx-autodoc-typehints",
"matplotlib",
"numpy>=1.18.0",
"scipy>=1.4.1",
"six>=1.13.0",
"scikit-learn>=0.22.2",
"Pillow>=6.0.0",
]
def read(rel_path):
here = os.path.abspath(os.path.dirname(__file__))
with codecs.open(os.path.join(here, rel_path), "r", encoding="utf-8") as fp:
return fp.read()
def get_version(rel_path):
for line in read(rel_path).splitlines():
if line.startswith("__version__"):
delim = '"' if '"' in line else "'"
return line.split(delim)[1]
raise RuntimeError("Unable to find version string.")
setup(
name="adversarial-robustness-toolbox",
version=get_version("art/__init__.py"),
description="Toolbox for adversarial machine learning.",
long_description=long_description,
long_description_content_type="text/markdown",
author="Irina Nicolae",
author_email="irinutza.n@gmail.com",
maintainer="Beat Buesser",
maintainer_email="beat.buesser@ie.ibm.com",
url="https://github.com/Trusted-AI/adversarial-robustness-toolbox",
license="MIT",
install_requires=install_requires,
extras_require={
"docs": docs_require,
"catboost": ["catboost"],
"gpy": ["GPy"],
"keras": ["keras", "h5py"],
"lightgbm": ["lightgbm"],
"mxnet": ["mxnet"],
"tensorflow": ["tensorflow", "tensorflow_addons", "h5py"],
"tensorflow_image": ["tensorflow", "tensorflow_addons", "h5py", "Pillow", "ffmpeg-python", "opencv-python"],
"tensorflow_audio": ["tensorflow", "tensorflow_addons", "h5py", "pydub", "resampy", "librosa"],
"pytorch": ["torch", "torchvision"],
"pytorch_image": ["torch", "torchvision", "kornia", "Pillow", "ffmpeg-python", "opencv-python"],
"pytorch_audio": ["torch", "torchvision", "torchaudio", "pydub", "resampy", "librosa"],
"xgboost": ["xgboost"],
"lingvo_asr": ["tensorflow-gpu==2.1.0", "lingvo==0.6.4", "pydub", "resampy", "librosa"],
"all": [
"mxnet",
"catboost",
"lightgbm",
"tensorflow",
"tensorflow-addons",
"h5py",
"torch",
"torchvision",
"xgboost",
"pandas",
"kornia",
"matplotlib",
"Pillow",
"statsmodels",
"pydub",
"resampy",
"ffmpeg-python",
"cma",
"librosa",
"opencv-python",
"numba",
],
"non_framework": [
"matplotlib",
"Pillow",
"statsmodels",
"pydub",
"resampy",
"ffmpeg-python",
"cma",
"pandas",
"librosa",
"opencv-python",
"pytest",
"pytest-flake8",
"pytest-mock",
"pytest-cov",
"requests",
"sortedcontainers",
"numba",
"timm",
"multiprocess",
]
},
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Topic :: Software Development :: Libraries",
"Topic :: Software Development :: Libraries :: Python Modules",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Security",
],
packages=find_packages(),
include_package_data=True,
)
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