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Stanislaw Adaszewski
4 years ago
2 changed files with 7 additions and 2 deletions
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| @@ -9,9 +9,14 @@ settings. | |||||
| Decagon-PyTorch is a PyTorch reimplementation of the algorithm. | Decagon-PyTorch is a PyTorch reimplementation of the algorithm. | ||||
| ## Citing | |||||
| If you use this code in your research please cite this repository as: | |||||
| Adaszewski S. (2020) https://code.adared.ch/sadaszewski/decagon-pytorch | |||||
| ## References | ## References | ||||
| 1. Zitnik, M., Agrawal, M., & Leskovec, J. (2018). | 1. Zitnik, M., Agrawal, M., & Leskovec, J. (2018). | ||||
| [Modeling polypharmacy side effects with graph convolutional networks](https://academic.oup.com/bioinformatics/article/34/13/i457/5045770) | [Modeling polypharmacy side effects with graph convolutional networks](https://academic.oup.com/bioinformatics/article/34/13/i457/5045770) | ||||
| Bioinformatics, 34(13), i457-i466. | Bioinformatics, 34(13), i457-i466. | ||||
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| @@ -109,7 +109,7 @@ def _wrap(obj, method_name): | |||||
| def main(): | def main(): | ||||
| dev = torch.device('cuda:0') | |||||
| dev = torch.device('cpu') | |||||
| data = load_data(dev) | data = load_data(dev) | ||||
| prep_d = prepare_training(data, TrainValTest(.8, .1, .1)) | prep_d = prepare_training(data, TrainValTest(.8, .1, .1)) | ||||
| _wrap(Model, 'build') | _wrap(Model, 'build') | ||||