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from pathlib import Path | |
from setuptools import find_packages, setup | |
if __name__ == "__main__": | |
with Path(Path(__file__).parent, "README.md").open(encoding="utf-8") as file: | |
long_description = file.read() | |
# TODO: This is a hack to get around the fact that we can't read the requirements.txt file, we should fix this. | |
# def _read_reqs(relpath): | |
# fullpath = os.path.join(Path(__file__).parent, relpath) | |
# with open(fullpath) as f: | |
# return [ | |
# s.strip() | |
# for s in f.readlines() | |
# if (s.strip() and not s.startswith("#")) | |
# ] | |
REQUIREMENTS = [ | |
"einops", | |
"einops-exts", | |
"transformers", | |
"torch==1.12.1", | |
"torchvision==0.13.1", | |
"pillow==9.3.0", | |
"more-itertools", | |
"datasets==2.9.0", | |
"braceexpand==0.1.7", | |
"webdataset", | |
"wandb==0.13.10", | |
"nltk", | |
"scipy", | |
"inflection", | |
"sentencepiece", | |
"open_clip_torch==2.20.0", | |
"opencv-python==4.7.0.68" | |
] | |
setup( | |
name="open_flamingo", | |
packages=find_packages(), | |
include_package_data=True, | |
version="0.0.2", | |
license="MIT", | |
description="An open-source framework for training large multimodal models", | |
long_description=long_description, | |
long_description_content_type="text/markdown", | |
data_files=[(".", ["README.md"])], | |
keywords=["machine learning"], | |
install_requires=REQUIREMENTS, | |
classifiers=[ | |
"Development Status :: 4 - Beta", | |
"Intended Audience :: Developers", | |
"Topic :: Scientific/Engineering :: Artificial Intelligence", | |
"License :: OSI Approved :: MIT License", | |
"Programming Language :: Python :: 3.9", | |
], | |
) | |