Looking at the example for how LBFGS needs a closure() function to be used (https://github.com/pytorch/examples/blob/master/time_sequence_prediction/train.py), is there a way I could plot the loss as well? Simply appending the loss calculated inside closure() to a list initialized outside closure doesn’t seem to work.
Do you get any error or why is it not working?
loss.item() to a list seems to work:
losses =  def closure(): optimizer.zero_grad() out = seq(input) loss = criterion(out, target) print('loss:', loss.item()) losses.append(loss.item()) loss.backward() return loss optimizer.step(closure)
My bad, it does seem to work indeed. Not quite sure what I missed last time since I tried the exact same thing and the list just stayed empty. Thanks a lot!