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?