Working loading and predicting with pretrained model + Added scaling in "pure" pytorch during forwarding
15216c3
| import setuptools | |
| setuptools.setup( | |
| name="protac_degradation_predictor", | |
| version="0.0.1", | |
| author="Stefano Ribes", | |
| url="https://github.com/ribesstefano/PROTAC-Degradation-Predictor", | |
| author_email="ribes.stefano@gmail.com", | |
| description="A package to predict PROTAC-induced protein degradation.", | |
| long_description=open("README.md").read(), | |
| packages=setuptools.find_packages(), | |
| install_requires=["torch", "pytorch_lightning", "scikit-learn", "imbalanced-learn", "rdkit-pypi", "pandas", "joblib", "h5py", "optuna", "torchmetrics"], | |
| classifiers=[ | |
| "Programming Language :: Python :: 3", | |
| "Programming Language :: Python :: 3.6", | |
| "License :: OSI Approved :: MIT License", | |
| "Operating System :: OS Independent", | |
| ], | |
| include_package_data=True, | |
| package_data={"": ["data/*.h5", "data/*.pkl", "data/*.csv", "models/*.ckpt"]}, | |
| ) |