hgraph2graph
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Hierarchical Generation of Molecular Graphs using Structural Motifs
Hello, I am following the the example for "Molecule generation pretraining procedure". first step "python get_vocab.py --ncpu 16 < data/chembl/all.txt > vocab.txt" is done with no error, but I am...
- Code is formatted now. - Code seems to work with newer chemprop versions.
`python finetune_generator.py --train ${ACTIVE_MOLECULES} --vocab data/chembl/vocab.txt --generative_model ckpt/chembl-pretrained/model.ckpt --chemprop_model ${YOUR_PROPERTY_PREDICTOR} --min_similarity 0.1 --max_similarity 0.5 --nsample 10000 --epoch 10 --threshold 0.5 --save_dir ckpt/finetune` The details about "chemprop_model" is not given properly....
After you generate the vocabulary in the first step of the [README](https://github.com/wengong-jin/hgraph2graph/blob/master/README.md), ``` python get_vocab.py --ncpu 16 < data/chembl/all.txt > vocab.txt ``` the next line should be: ``` python preprocess.py...
Hi After run the example: python generate.py --vocab data/chembl/vocab.txt --model ckpt/chembl-pretrained/model.ckpt --nsamples 1000 I got the error when passing the argument --nsamples _**usage: generate.py [-h] --vocab VOCAB [--atom_vocab ATOM_VOCAB] --model...
Added tqdm library in dependencies. Fixed nsample flag.
rdkit version: 2021.03.3 (didn't check in other versions) Doing `python get_vocab.py --ncpu 16 < aromatic.txt > vocab.txt` with aromatic SMILES, an error occurs because of Chem.Kekulize function. In chemutils.py, Before:...
Hi Everyone, The pretrained chembl model has been provided which is really helpful. But to generate the new lead compounds, similar to that shown in step 4 in molecular translation...
Hi Wengong, In the decode process, it seems all the assm_labels are 0. Why do we need to train the get_assm_score if "#the label is always the first of assm_cands"?...
Is there a way to use constraint optimization to find novel molecules with higher desired property? I read the paper about your previous work (Junction Tree Variational Autoencoder) and wonder...