I want to learn the parameters of A & B.
I am trying to implement a Phase Functioned Neural Net as described in Appendix B of this 8 paper.
I am passing parameters of A and B to the optimiser.
I don’t care about parameters of C since I use it as a temporary network (probably don’t need the C network)
C shouldn’t be a network (or at least shouldn’t change in place) since then 2 forward passes would be a problem.
I am looking for a simple way to make a forward pass using linear combination of parameters of A & B, and then a backward pass to update parameters of both these networks