code: def test_homogenousgraph_multi_block_results():
      dgl_g = dgl.graph(data=([1, 2, 2, 3, 4, 5], [0, 0, 1, 2, 2, 3]))
      cugraph_g = cugraph_dgl.cugraph_storage_from_heterograph(
          dgl_g, single_gpu=True
      )
      train_nid = th.tensor([0])
      cugraph_dgl_output = sample_cugraph_dgl_graphs(
          cugraph_g, train_nid, [2, 2, 2]
      )
      assert (
          cugraph_dgl_output[0]["blocks"][0].num_dst_nodes()
          == cugraph_dgl_output[0]["blocks"][1].num_src_nodes()
      )
      assert (
          cugraph_dgl_output[0]["blocks"][1].num_dst_nodes()
          == cugraph_dgl_output[0]["blocks"][2].num_src_nodes()
      )
  
file_path: cugraph/python/cugraph-dgl/tests/test_dataloader.py
imports: import pytest
  import dgl
  import torch
  from cugraph_dgl import cugraph_storage_from_heterograph
  import tempfile
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: test_homogenousgraph_multi_block_results() without return types