I’m fairly new to pytorch and currently i would like to train a model wich consists in the following:
I have one already trained model (net1) wich receives as an input the output of a untrained model (net2), and generates on output. (net2 → net1 → output)
Then my question the is, is it possible compute the gradient through net1 and net2 but only run an optimizer.step() and update the weights of net2?