Hi, my question might be bit odd but i’m hoping it is possible with pytorch
Say i have two networks, the first of which outputs a bunch of values, one for each parameter of the second network (say a classification network) i then add these values to the parameters of the second network and perform a forward pass of the second network and compute a loss, is it possible to backprop the loss through to the first network to perform an optimization step?
Thanks