torch.Tensor.to_sparse
Tensor.to_sparse(sparseDims) -> Tensor
Returns a sparse copy of the tensor.  PyTorch supports sparse
   tensors in coordinate format.
Parameters:
      sparseDims (int, optional) -- the number of sparse
      dimensions to include in the new sparse tensor
Example:
  >>> d = torch.tensor([[0, 0, 0], [9, 0, 10], [0, 0, 0]])
  >>> d
  tensor([[ 0,  0,  0],
          [ 9,  0, 10],
          [ 0,  0,  0]])
  >>> d.to_sparse()
  tensor(indices=tensor([[1, 1],
                         [0, 2]]),
         values=tensor([ 9, 10]),
         size=(3, 3), nnz=2, layout=torch.sparse_coo)
  >>> d.to_sparse(1)
  tensor(indices=tensor([[1]]),
         values=tensor([[ 9,  0, 10]]),
         size=(3, 3), nnz=1, layout=torch.sparse_coo)

to_sparse(*, layout=None, blocksize=None, dense_dim=None) -> Tensor
Returns a sparse tensor with the specified layout and blocksize.