Difference between tensor.permute and tensor.view in PyTorch?
tensor.permute() permutes the order of the axes of a tensor.
tensor.view() reshapes the tensor (analogous to numpy.reshape) by reducing/expanding the size of each dimension (if one increases, the others must decrease).
What is the difference between tensor.permute() and tensor.view()? 
They seem to do the same thing.