Molecular AutoEncoder in PyTorch
$ git clone https://github.com/cxhernandez/molencoder.git && cd molencoder
$ python setup.py install$ molencoder download --dataset chembl22$ molencoder train --dataset data/chembl22.h5Add --cuda flag to enable CUDA. Add --cont to continue training a model from a checkpoint file.
A pre-trained reference model is available in the ref/ directory. Currently, it performs with ~98% accuracy on the validation set after 100 epochs of training. However, if you succeed at training a better model, feel free to submit a pull request!
- Implement encoder
- Implement decoder
- Add download command
- Add train command
- Add encode command
- Add decode command
- Add pre-trained model
- Original paper by Gómez-Bombarelli, et al.
- keras-molecules by Max Hodak
- DeepChem
- PyTorch