code: def test_citeseer(get_dataset):
      dataset = get_dataset(name="CiteSeer")
      loader = DataLoader(dataset, batch_size=len(dataset))
  
      assert len(dataset) == 1
      assert str(dataset) == "CiteSeer()"
  
      for batch in loader:
          assert batch.num_graphs == len(batch) == 1
          assert batch.num_nodes == 3327
          assert batch.num_edges / 2 == 4552
  
          assert list(batch.x.size()) == [batch.num_nodes, 3703]
          assert list(batch.y.size()) == [batch.num_nodes]
          assert batch.y.max() + 1 == 6
          assert batch.train_mask.sum() == 6 * 20
          assert batch.val_mask.sum() == 500
          assert batch.test_mask.sum() == 1000
          assert (
              batch.train_mask & batch.val_mask & batch.test_mask
          ).sum() == 0
          assert list(batch.batch.size()) == [batch.num_nodes]
          assert batch.ptr.tolist() == [0, batch.num_nodes]
  
          assert batch.has_isolated_nodes()
          assert not batch.has_self_loops()
          assert batch.is_undirected()
  
imports: from torch_geometric.loader import DataLoader
  from torch_geometric.testing import onlyOnline
label_desc: Use image node_id 1 for calling a global function with example usage: test_citeseer(get_dataset) without return types