code: def _create_homogeneous():
      s = torch.randint(0, 200, (1000,))
      d = torch.randint(0, 200, (1000,))
      g = dgl.graph((s, d), num_nodes=200)
      reverse_eids = torch.cat(
          [torch.arange(1000, 2000), torch.arange(0, 1000)]
      )
      seed_edges = torch.arange(0, 1000)
      return g, reverse_eids, seed_edges
  
file_path: dgl/tests/python/pytorch/dataloading/test_spot_target.py
imports: from collections.abc import Mapping
  import dgl
  import numpy
  import pytest
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: _create_homogeneous() and returns: g,  reverse_eids,  seed_edges