Code for our paper Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation .
We use pytorch 0.4.1 and python 3.
Run the training by:
python vae
The default logdir is /mnt/Data/DL/tmp/beta_vae_mol， which is specified in the file /base_classes/trainer.py.
After training, you can run the testing by:
python vae --restore=path_to_checkpoint_dir/150
Thanks for the partialsmiles package, we can guide the molecule sequence generataion now. Enable guiding by the partialsmiles in generation procedure by:
python vae --restore=path_to_checkpoint_dir/150 --partialsmiles
Our implementation is modified on the code from https://github.com/DavidJanz/molecule_grammar_rnn.
If you find our code useful, please cite our paper:
@inproceedings{yan2020re,
title={Re-balancing variational autoencoder loss for molecule sequence generation},
author={Yan, Chaochao and Wang, Sheng and Yang, Jinyu and Xu, Tingyang and Huang, Junzhou},
booktitle={Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics},
pages={1--7},
year={2020}
}
@article{yan2022molecule,
title={Molecule Sequence Generation with Rebalanced Variational Autoencoder Loss},
author={Yan, Chaochao and Yang, Jinyu and Ma, Hehuan and Wang, Sheng and Huang, Junzhou},
journal={Journal of Computational Biology},
year={2022},
publisher={Mary Ann Liebert}
}