def METHOD_NAME(num_workers):
    data = HeteroData()
    data['p'].x = torch.randn(100, 128)
    data['a'].x = torch.randn(200, 128)
    data['p', 'a'].edge_index = get_random_edge_index(100, 200, 500)
    data['p'].edge_attr = torch.randn(500, 32)
    data['a', 'p'].edge_index = get_random_edge_index(200, 100, 400)
    data['a', 'p'].edge_attr = torch.randn(400, 32)
    loader = DataLoader([data, data, data, data], batch_size=2, shuffle=False,
                        num_workers=num_workers)
    assert len(loader) == 2
    for batch in loader:
        assert batch.num_graphs == len(batch) == 2
        assert batch.num_nodes == 600
        for store in batch.stores:
            assert id(batch) == id(store._parent())