The labels are atom type and bond type, and each loss was calculated as a cross entropy loss function where the sum of losses is the overall loss. The ratio of train/test data was 4:1, and parameters were updated with the Adam optimizer. The model was trained in a teacherforcing 46 manner, in which label data were used as inputs when there is a dependency between the inputs. The input for the bond prediction was not the output of the atom prediction module but the label of the atom, because the prediction of the bond depends on the prediction of the atom. The other training settings were as follows.