Hi,
I have a network which outputs 2 values, x and y.  I intend to not use the output y for training. Will the backward pass add weights with garbage values due to y branch?
Below is just an illustration of the model at hand.
model = common_model -> [head_x, head_y]
The optimisers for x and y head are initialized with model.parameters() field. And I only call opt_x.zero_grad() before each forward pass.
Any things to take care of for such situations? Like calling zero_grad() for opt_y as well?