I'm learning to build a customized sequence-to-sequence model with keras, and have been reading some codes that other people wrote, for example here. I got confused in the call method regarding constants. There is the keras "Note on passing external constants to RNNs", however I'm having trouble to understand what the constants are doing to the model.
I did go through the attention model and the pointer network papers, but maybe I've missed something.
Any reference to the modeling details would be appreciated! Thanks in advance.