code: def _create_split_dict(tensor):
      min_value = tensor.min()
      max_value = tensor.max()
      indices = torch.arange(
          start=min_value + 1,
          end=max_value + 1,
          device=tensor.device,
      )
      split_dict = {i: {} for i in range(min_value, max_value + 1)}
      return split_dict, indices
  
imports: from __future__ import annotations
  from typing import List, Tuple, Dict, Optional
  from collections import defaultdict
  import cudf
  from cugraph.utilities.utils import import_optional
  from cugraph_dgl.nn import SparseGraph
label_desc: Use image node_id 4 for calling a global function with example usage: _create_split_dict(tensor) and returns: split_dict,  indices