code: def test_dynamic_hetero_graph_temporal_signal_edges():
      dataset = DynamicHeteroGraphTemporalSignal(
          [{("author", "writes", "paper"): np.array([[0, 1], [1, 0]])}],
          [{("author", "writes", "paper"): np.array([[0.1], [0.1]])}],
          [
              {
                  "author": np.array([[0], [0]]),
                  "paper": np.array([[0], [0], [0]]),
              }
          ],
          [None],
      )
      for snapshot in dataset:
          assert snapshot.edge_stores[0]["edge_index"].shape == (2, 2)
          assert snapshot.edge_stores[0]["edge_attr"].shape == (2, 1)
          assert (
              snapshot.edge_stores[0]["edge_index"].shape[0]
              == snapshot.edge_stores[0]["edge_attr"].shape[0]
          )
  
imports: import numpy
  import networkx
  from torch_geometric_temporal.signal import temporal_signal_split
  from torch_geometric_temporal.signal import StaticGraphTemporalSignal
  from torch_geometric_temporal.signal import DynamicGraphTemporalSignal
  from torch_geometric_temporal.signal import DynamicGraphStaticSignal
  from torch_geometric_temporal.signal import StaticHeteroGraphTemporalSignal
  from torch_geometric_temporal.signal import DynamicHeteroGraphTemporalSignal
  from torch_geometric_temporal.signal import DynamicHeteroGraphStaticSignal
  from torch_geometric_temporal.dataset import METRLADatasetLoader, PemsBayDatasetLoader
  from torch_geometric_temporal.dataset import ChickenpoxDatasetLoader, PedalMeDatasetLoader, WikiMathsDatasetLoader, EnglandCovidDatasetLoader
  from torch_geometric_temporal.dataset import TwitterTennisDatasetLoader, MontevideoBusDatasetLoader, MTMDatasetLoader
  from torch_geometric_temporal.dataset import WindmillOutputLargeDatasetLoader, WindmillOutputMediumDatasetLoader, WindmillOutputSmallDatasetLoader
label_desc: Use image node_id 23 for calling a global function with example usage: test_dynamic_hetero_graph_temporal_signal_edges() without return types