torch.Tensor.col_indices
Tensor.col_indices() -> IntTensor
Returns the tensor containing the column indices of the "self"
   tensor when "self" is a sparse CSR tensor of layout "sparse_csr".
   The "col_indices" tensor is strictly of shape ("self".nnz()) and of
   type "int32" or "int64".  When using MKL routines such as sparse
   matrix multiplication, it is necessary to use "int32" indexing in
   order to avoid downcasting and potentially losing information.
Example::
      >>> csr = torch.eye(5,5).to_sparse_csr()
      >>> csr.col_indices()
      tensor([0, 1, 2, 3, 4], dtype=torch.int32)