I know that in pytorch 1.5 to() and clone() can preserve formats and therefore we can send non-contiguous tensors between devices.
I wonder, what is the case for copy_()?  can we send non-contagious tensors with it?
If not, is there any suggested workaround for avoiding copy?
for example
a = torch.randn(10,1, device="cuda:1").share_memory_()
b = torch.randn(10,2, device="cuda:0")
b = torch.transpose(b, 0,1)
a.copy_(b)  # is it OK?

In the example above we want to avoid using to()/clone() to avoid creating a new tensor and moving it to shared memory.