code: def test_find_reverse_edges_bi_reverse_types():
      edges = {
          "A:r:B": (torch.tensor([1, 5]), torch.tensor([2, 5])),
          "B:rr:A": (torch.tensor([3]), torch.tensor([3])),
      }
      edges = gb.add_reverse_edges(
          edges, {"A:r:B": "B:rr:A", "B:rr:A": "A:r:B"}
      )
      expected_edges = {
          "A:r:B": (torch.tensor([1, 5, 3]), torch.tensor([2, 5, 3])),
          "B:rr:A": (torch.tensor([3, 2, 5]), torch.tensor([3, 1, 5])),
      }
      assert torch.equal(edges["A:r:B"][0], expected_edges["A:r:B"][0])
      assert torch.equal(edges["A:r:B"][1], expected_edges["A:r:B"][1])
      assert torch.equal(
          edges["B:rr:A"][0], expected_edges["B:rr:A"][0]
      )
      assert torch.equal(
          edges["B:rr:A"][1], expected_edges["B:rr:A"][1]
      )
  
file_path: dgl/tests/python/pytorch/graphbolt/test_graphbolt_utils.py
imports: import backend
  import dgl.graphbolt
  import pytest
  import torch
label_desc: Use image node_id 3 for calling a global function with example usage: test_find_reverse_edges_bi_reverse_types() without return types