Pytorch, Deep Learning, Optimization, Tensorboard, Deep Dives.
torch.autocast(device_type='cuda', dtype=torch.float16): outputs = model(inputs) loss = criterion(outputs, labels) # Note - torch.cuda.amp.GradScaler() may be required optimizer.zero_grad(set_to_none=True) loss.backward() optimizer.step() The impact to the Tensor Core utilization is displayed in