code: def test_dynamic_hetero_graph_static_signal_batch_edges():
      dataset = DynamicHeteroGraphStaticSignalBatch(
          [{("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],
          [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 StaticGraphTemporalSignalBatch
  from torch_geometric_temporal.signal import DynamicGraphTemporalSignalBatch
  from torch_geometric_temporal.signal import DynamicGraphStaticSignalBatch
  from torch_geometric_temporal.signal import StaticHeteroGraphTemporalSignalBatch
  from torch_geometric_temporal.signal import DynamicHeteroGraphTemporalSignalBatch
  from torch_geometric_temporal.signal import DynamicHeteroGraphStaticSignalBatch
label_desc: Use image node_id 22 for calling a global function with example usage: test_dynamic_hetero_graph_static_signal_batch_edges() without return types