Thanks for the response!
So I already have the predicted embeddings, I need to back-propagate the results. But when I pass in the two embeddings (one being the predicted embeddings, the other being the target embedding) to the loss function, I get this:
AssertionError: nn criterions don't compute the gradient w.r.t. targets - please mark these variables as volatile or not requiring gradients
I’d just like to know the best way to compute loss then back-propagate AFTER receiving the predicted output, which is also an embedded vector. Is it clear what I’m asking? Thanks again for your help.