CNSMolGen consists of two basic models (Fig. ), the first model is mainly a bidirectional RNNs model based on SMILES . Its bidirectionality and holistic nature makes it more suitable for molecular generation process compared to traditional RNNs, also known as pre-trained model. And the second one is the transfer model based on the same architecture as the previous model and used to migrate the general knowledge to learn the focused knowledge by sharing the previous network and reweighting the layers. Here, to illustrate the difference between the pre-trained model in CNSMolGen and the traditional RNN, we compare their objective functions. The objective function of the classical RNN is given by