Performance, Pytorch, Deep Learning, Artificial Intelligence, Tensorboard.
(1 + 4 + 3) * 1: break outputs = model(inputs) loss = criterion(outputs, labels) optimizer.zero_grad(set_to_none=True) loss.backward() optimizer.step() prof.step() If you were to naively run this training script, you would probably see high GPU (~90%) utilization and not know that there was