torch.Tensor.to_sparse_csc
Tensor.to_sparse_csc() -> Tensor
Convert a tensor to compressed column storage (CSC) format.  Except
   for strided tensors, only works with 2D tensors.  If the "self" is
   strided, then the number of dense dimensions could be specified,
   and a hybrid CSC tensor will be created, with dense_dim dense
   dimensions and self.dim() - 2 - dense_dim batch dimension.
Parameters:
      dense_dim (int, optional) -- Number of dense
      dimensions of the resulting CSC tensor.  This argument should be
      used only if "self" is a strided tensor, and must be a value
      between 0 and dimension of "self" tensor minus two.
Example:
  >>> dense = torch.randn(5, 5)
  >>> sparse = dense.to_sparse_csc()
  >>> sparse._nnz()
  25

  >>> dense = torch.zeros(3, 3, 1, 1)
  >>> dense[0, 0] = dense[1, 2] = dense[2, 1] = 1
  >>> dense.to_sparse_csc(dense_dim=2)
  tensor(ccol_indices=tensor([0, 1, 2, 3]),
