code: def test_discrete_train_test_split_static():
      loader = ChickenpoxDatasetLoader()
      dataset = loader.get_dataset()
      train_dataset, test_dataset = temporal_signal_split(dataset, 0.8)
  
      for epoch in range(2):
          for snapshot in train_dataset:
              assert snapshot.edge_index.shape == (2, 102)
              assert snapshot.edge_attr.shape == (102,)
              assert snapshot.x.shape == (20, 4)
              assert snapshot.y.shape == (20,)
  
      for epoch in range(2):
          for snapshot in test_dataset:
              assert snapshot.edge_index.shape == (2, 102)
              assert snapshot.edge_attr.shape == (102,)
              assert snapshot.x.shape == (20, 4)
              assert snapshot.y.shape == (20,)
  
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 40 for calling a global function with example usage: test_discrete_train_test_split_static() without return types