Optimization, Pytorch, Machine Learning, Deep Learning, Tensorboard.
built-in torch.nn.CrossEntropyLoss which we now evaluate and compare with our custom loss implementation. criterion = torch.nn.CrossEntropyLoss().cuda(device) The resultant step time is a new low of 8.5 milliseconds, as shown below: Trace View Following Optimization #6 (Captured by Author)