RNN-based models must learn how to generate SMILES and how to create molecules that appear in GDB-13. An ideal model is an abstract model that samples molecules from GDB-13 and only from GDB-13. Formally, the probability of sampling any molecule in the ideal model follows a uniform probability distribution with 𝑝 = |𝐺𝐷𝐵 3| = 1.02 • 10 9 . Due to the probabilistic nature of RNNs, no trained model will be able to have the same behavior, thus an ideal model serves as an upper bound.