The repository contains an implementation of the Molecular Transformer in Pytorch Lightning.
The repository also contains the code to accompany the manuscript
"Accelerating the inference of string generation-based chemical reaction models for industrial applications".
The idea of the manuscript is that reaction product prediction and single-step retrosynthesis with the Molecular Transformer
can be accelerated by ~3 times on inference without losing accuracy.
Create a new isolated environment with Python 3.10 and install the necessary packages:
pip install lightning
pip install jsonargparse[signatures]
pip install rdkit
pip install tensorboard
pip install gdown
pip install -e .For reaction prediction, we used USPTO_MIT mixed from the Molecular Transformer paper. For single-step retrosynthesis, we used USPTO50k as prepared in the RSMILES paper.
Download USPTO MIT mixed:
THIS_REPO_PATH=$(pwd) # The full path to this repository
gdown https://drive.google.com/drive/folders/1fJ7Hm55IDevIi5Apna7v-rQBQStTH7Yg -O data/MIT_mixed --folder
cd data/MIT_mixed
python3 detokenize.py
cd $THIS_REPO_PATHDownload USPTO 50K and augment it using RSMILES augmentation.
Clone the RSMILES repository to some path in your system.
pip install pandas textdistance
THIS_REPO_PATH=$(pwd) # The full path to this repository
RSMILES_PATH=../retrosynthesis # as an example; the path to the RSMILES repository
gdown https://drive.google.com/drive/folders/1la4OgBKgm2K-IRwuV-GHUNjN3bcCrl6v -O ${RSMILES_PATH}/dataset/USPTO_50K --folder
cd ${RSMILES_PATH}
AUGMENTATIONS=20
PROCESSES=8
python3 preprocessing/generate_PtoR_data.py -augmentation ${AUGMENTATIONS} -processes ${PROCESSES} -test_except
python3 preprocessing/generate_PtoR_data.py -augmentation 1 -processes ${PROCESSES} -test_only -canonical
mv dataset/USPTO_50K_PtoR_aug${AUGMENTATIONS} ${THIS_REPO_PATH}/data # The augmented dataset is now in this repository
mv dataset/USPTO_50K_PtoR_aug1 ${THIS_REPO_PATH}/data
cd $THIS_REPO_PATHThe file main.py calls a Pytorch Lightning model for either training or inference.
The directory scripts contains bash scripts for reaction product prediction and single-step retrosynthesis with speculative decoding.
Trained checkpoints and config files are available at Google Drive. Download reaction prediction checkpoints:
mkdir checkpoints
mkdir checkpoints/reaction_prediction
gdown https://drive.google.com/drive/folders/1sBiVgFZyD4F42nVqR835-0Tl90LkQvU9 -O checkpoints/reaction_prediction --folderDownload single-step retrosynthesis checkpoints
mkdir checkpoints/single_step_retrosynthesis
gdown https://drive.google.com/drive/folders/1v4pKYWlE0qNA-ksa7yX55i7qMeesURON -O checkpoints/single_step_retrosynthesis --folder