In practice, a molecule may be represented by several graphs differing by the order of the atoms. To augment the available data, each SMILES representation of the molecules is randomized 100 times, and all the corresponding graphs are used to train the models. Although we understand that this may create redundancy for small molecules (less possible SMILES representations and consequently less possible graphs), this will virtually increase the dataset size. This data augmentation ensures that all the molecules are equally represented while also ensuring that any representation of the same molecules would be considered.