Solved by ptrblck in post #4 
              
              
                Instead of loading real data you could initialize random data, push it to the GPU and profile the training loop without the data loading: 
# for a multi-class classification
data = torch.randn(batch_size, channels, height, width, device='cuda')
target = torch.randint(0, nb_classes, (batch_size,), d…