Thanks a lot for your reply! Actually, using PyTorch Profiler, I was able to have a look at the GPU memory, which nicely shows the memory consumption of a training session.
Additionally, I included the non_blocking=True statement, with which I was finally able to see the executed functions without any copying execution. I even gained a few ms performance increase. 
 x, y = x.to(device, non_blocking=True), y.to(device, non_blocking=True)