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setup.py
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setup.py
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from setuptools import setup, find_packages
exec(open('GraphDiffusion/version.py').read())
setup(
name = 'GraphDiffusion',
packages = find_packages(exclude=[]),
include_package_data = True,
version = __version__,
license='MIT',
description = 'Graph Generation using Diffusion models and Autoregressive Transformer Models',
author = 'Markus J Buehler',
author_email = 'mbuehler@MIT.EDU',
long_description_content_type = 'text/markdown',
url = 'https://github.com/lamm-mit/GraphDiffusion',
keywords = [
'artificial intelligence',
'deep learning',
'transformers',
'graph generation',
'scientific machine learning',
'dynamical processes',
'denoising-diffusion',
'materials science'
],
install_requires=[
'accelerate',
'click',
'einops>=0.4',
'einops-exts',
'ema-pytorch>=0.0.3',
'fsspec',
'kornia',
'numpy',
'packaging',
'pillow',
'pydantic',
'pytorch-lightning',
'pytorch-warmup',
'sentencepiece',
'torch',
'torchvision',
'transformers',
'tqdm',
'jupyterlab',
'matplotlib',
'scikit-learn',
'pandas',
'IProgress',
'ipywidgets',
'opencv-python',
'seaborn',
'torch-geometric',
],
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3.8',
],
)