The bond prediction module takes the predicted atom and hidden states of the nodes as input, and predicts the bonds through the RNN layer. The initial state vector s of the RNN is the concatenation of the vector obtained by transforming the predicted atoms with the Embedding layer (Emb(•)) and the hidden representation of the graph h g . The input of the RNN is the hidden state vector of nodes h n arranged as a series of data according to the BFS order of nodes in the input graph. The output is the type of bonds as a probability, whose dimension is (number of bond types)+1 including a label indicating that there is no bond. s = concat(h g , Emb(y a ))