torch.transpose
torch.transpose(input, dim0, dim1) -> Tensor
Returns a tensor that is a transposed version of "input". The given
   dimensions "dim0" and "dim1" are swapped.
If "input" is a strided tensor then the resulting "out" tensor
   shares its underlying storage with the "input" tensor, so changing
   the content of one would change the content of the other.
If "input" is a sparse tensor then the resulting "out" tensor does
   not share the underlying storage with the "input" tensor.
If "input" is a sparse tensor with compressed layout (SparseCSR,
   SparseBSR, SparseCSC or SparseBSC) the arguments "dim0" and "dim1"
   must be both batch dimensions, or must both be sparse dimensions.
   The batch dimensions of a sparse tensor are the dimensions
   preceding the sparse dimensions.
Note:
 Transpositions which interchange the sparse dimensions of a
 *SparseCSR* or *SparseCSC* layout tensor will result in the
