As a forward response prediction model P = g(S), we employed Molecular Transformer , which is known to be a state-of-the-art model. This attention-based neural translation model defines a translation between the SMILES strings of reactants and their products. For simplicity, reagents were removed from the model input. SMILES strings for multiple reactants were input into the model as separated by periods ".". The SMILES strings were all canonicalized using RDKit. The inputs were tokenized with the regular expression according to the original paper of Molecular Transformer.