Solved by ptrblck in post #5 
              
              
                Thanks! I could reproduce this issue and guess an internal matmul kernel might run into an overflow. 
As a workaround, use the CUDA10.2 binaries, which ship with cudnn7.6.5.32 or alternatively you could also build PyTorch from source using cudnn8.1. 
I’ve forwarded the issue to the cudnn team, which…