code: def test_heterograph_multi_block_results():
      data_dict = {
          ("B", "BA", "A"): (
              [1, 2, 3, 4, 5, 6, 7, 8],
              [0, 0, 0, 0, 1, 1, 1, 1],
          ),
          ("C", "CA", "A"): (
              [1, 2, 3, 4, 5, 6, 7, 8],
              [0, 0, 0, 0, 1, 1, 1, 1],
          ),
          ("A", "AA", "A"): ([1], [0]),
      }
      dgl_g = dgl.heterograph(data_dict)
      cugraph_g = cugraph_dgl.cugraph_storage_from_heterograph(
          dgl_g, single_gpu=True
      )
      train_nid = {"A": th.tensor([0])}
      cugraph_dgl_output = sample_cugraph_dgl_graphs(
          cugraph_g, train_nid, [10, 10]
      )
      assert (
          cugraph_dgl_output[0]["blocks"][0].num_dst_nodes()
          == cugraph_dgl_output[0]["blocks"][1].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 5 for calling a global function with example usage: test_heterograph_multi_block_results() without return types