code: def test_static_graph_temporal_signal_additional_attrs():
      dataset = StaticGraphTemporalSignal(
          None,
          None,
          [None],
          [None],
          optional1=[np.array([1])],
          optional2=[np.array([2])],
      )
      assert dataset.additional_feature_keys == [
          "optional1",
          "optional2",
      ]
      for snapshot in dataset:
          assert snapshot.optional1.shape == (1,)
          assert snapshot.optional2.shape == (1,)
  
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 9 for calling a global function with example usage: test_static_graph_temporal_signal_additional_attrs() without return types