dmlc--dgl
Quan (Andy) Gan
f5eb80d221
* clean commit * oops forgot the most important files * use einsum * copy feature from frontier to block * Revert "copy feature from frontier to block" This reverts commit 5224ec963eb6a3ef1b6ab74d8ecbd44e4e42f285. * temp fix * unit test * fix * revert jtnn * lint * fix win64 * docstring fixes and doc indexing * revert einsum in sparse bidecoder * fix some examples * lint * fix due to some tediousness in remove_edges * addresses comments * fix * more jtnn fixes * fix
Junction Tree VAE - example for training
This is a direct modification from https://github.com/wengong-jin/icml18-jtnn
Dependencies
- PyTorch 0.4.1+
- RDKit=2018.09.3.0
- requests
How to run
To run the model, use
python3 vaetrain_dgl.py
The script will automatically download the data, which is the same as the one in the original repository.
To disable CUDA, run with NOCUDA variable set:
NOCUDA=1 python3 vaetrain_dgl.py
To decode for new molecules, run
python3 vaetrain_dgl.py -T
Currently, decoding involves encoding a training example, sampling from the posterior distribution, and decoding a molecule from that.