where ϵ is a predefined tolerance threshold that weakens the monotonicity requirement. We also provide two implementations of relaxed success rate, which defines different tolerance variables ϵ with local relaxed constraint (RSR-L) and global relaxed constraint (RSR-G). For global constraint, we obtain ϵ by calculating the possible values (ranges) of the molecular properties in the training dataset, while for local constraint, we obtain ϵ by calculating the possible values (ranges) of the molecular properties only in the specific manipulation paths. The formulation of RSR-L and RSR-G is as follows: