code: def _create_homogeneous_cugraph_dgl_nn_sparse_graph(
      tensor_d, seednodes_range
  ):
      max_src_nodes = tensor_d["sources_range"]
      max_dst_nodes = tensor_d["destinations_range"]
      if seednodes_range is not None:
          max_dst_nodes = max(max_dst_nodes, seednodes_range)
      size = (max_src_nodes + 1, max_dst_nodes + 1)
      sparse_graph = cugraph_dgl.nn.SparseGraph(
          size=size,
          src_ids=tensor_d["sources"],
          dst_ids=tensor_d["destinations"],
          formats=["csc"],
          reduce_memory=True,
      )
      return sparse_graph
  
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 10 for calling a global function with example usage: _create_homogeneous_cugraph_dgl_nn_sparse_graph(tensor_d, seednodes_range) and returns: sparse_graph