Hello everyone,
I am trying to train a model that uses parameters that are a sum of two sets weights and I want to to train only one set of weights. That is, for every weight w = w_1 + w_2, where w_2 is a constant and w_1 is to be optimized using an optimizer. Thus, in the forward step w is used to compute the loss, but in the backward step only w_1 is adjusted. Is this possible?