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https://github.com/cxhernandez/molencoder
Molecular AutoEncoder in PyTorch
https://github.com/cxhernandez/molencoder
autoencoder computational-chemistry deep-learning python pytorch
Last synced: about 2 months ago
JSON representation
Molecular AutoEncoder in PyTorch
- Host: GitHub
- URL: https://github.com/cxhernandez/molencoder
- Owner: cxhernandez
- License: mit
- Created: 2017-05-20T03:14:59.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2020-05-13T19:23:25.000Z (about 4 years ago)
- Last Synced: 2024-01-25T20:09:08.651Z (4 months ago)
- Topics: autoencoder, computational-chemistry, deep-learning, python, pytorch
- Language: Python
- Size: 49.8 MB
- Stars: 84
- Watchers: 7
- Forks: 17
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- Awesome-pytorch-list - molencoder
- Awesome-pytorch-list-CNVersion - molencoder
- awesome-python-machine-learning-projects - Molecular Autoencoder - compression of ATLAS trigger jet events using autoencoders (Chemistry)
README
# MolEncoder
Molecular AutoEncoder in PyTorch
## Install
```bash
$ git clone https://github.com/cxhernandez/molencoder.git && cd molencoder
$ python setup.py install
```
## Download Dataset
```bash
$ molencoder download --dataset chembl22
```
## Train
```bash
$ molencoder train --dataset data/chembl22.h5
```
Add `--cuda` flag to enable CUDA. Add `--cont` to continue training a model from a checkpoint file.
## Pre-Trained Model
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!
## TODO
- [x] Implement encoder
- [x] Implement decoder
- [x] Add download command
- [x] Add train command
- [ ] Add encode command
- [ ] Add decode command
- [x] Add pre-trained model
## Shoutouts
+ [Original paper](https://arxiv.org/abs/1610.02415) by Gómez-Bombarelli, et al.
+ [keras-molecules](https://github.com/maxhodak/keras-molecules) by Max Hodak
+ [DeepChem](https://github.com/deepchem/deepchem)
+ [PyTorch](pytorch.org)