code: def saint_subgraph(
      src: SparseTensor, node_idx: torch.Tensor
  ) -> Tuple[SparseTensor, torch.Tensor]:
      row, col, value = src.coo()
      rowptr = src.storage.rowptr()
  
      data = torch.ops.torch_sparse.saint_subgraph(
          node_idx, rowptr, row, col
      )
      row, col, edge_index = data
  
      if value is not None:
          value = value[edge_index]
  
      out = SparseTensor(
          row=row,
          rowptr=None,
          col=col,
          value=value,
          sparse_sizes=(node_idx.size(0), node_idx.size(0)),
          is_sorted=True,
      )
  
      return out, edge_index
  
label_desc: Use image node_id 1 for calling a global function with example usage: saint_subgraph(src, node_idx) and returns: out,  edge_index