I face a problem about copy tensor to cpu.
I test same step on V100 and P100 card.  Same environment.
On V100 card machine, the .cpu() step only cost less than 0.01s.
But on P100 card machine, this single step cost 5 second at most(based on the length of tensor, one dimesion length about 10,0000)
Is that only about the GPU? I use CUDA 9 and pytorch 1.0.0.