torch.Tensor.to_sparse_csr
Tensor.to_sparse_csr(dense_dim=None) -> Tensor
Convert a tensor to compressed row storage format (CSR).  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 CSR 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 CSR 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_csr()
  >>> sparse._nnz()
  25

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