code: def test_fake_dataset(num_graphs, edge_dim, task):
      dataset = FakeDataset(
          num_graphs, edge_dim=edge_dim, task=task, global_features=3
      )
  
      if num_graphs > 1:
          assert str(dataset) == f"FakeDataset({num_graphs})"
      else:
          assert str(dataset) == "FakeDataset()"
  
      assert len(dataset) == num_graphs
  
      data = dataset[0]
  
      assert data.num_features == 64
  
      if edge_dim == 0:
          assert len(data) == 4
      elif edge_dim == 1:
          assert len(data) == 5
          assert data.edge_weight.size() == (data.num_edges,)
          assert (
              data.edge_weight.min() >= 0 and data.edge_weight.max() < 1
          )
      else:
          assert len(data) == 5
          assert data.edge_attr.size() == (data.num_edges, edge_dim)
          assert data.edge_attr.min() >= 0 and data.edge_attr.max() < 1
  
      assert data.y.min() >= 0 and data.y.max() < 10
      if task == "node" or (task == "auto" and num_graphs == 1):
          assert data.y.size() == (data.num_nodes,)
      else:
          assert data.y.size() == (1,)
  
      assert data.global_features.size() == (3,)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_fake_dataset(num_graphs, edge_dim, task) without return types