code: def get_edge_array(node_count, node_start):
      edges = []
      for edge in nx.gnp_random_graph(node_count, 0.1).edges():
          edges.append([edge[0] + node_start, edge[1] + node_start])
      return np.array(edges)
  
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 1 for calling a global function with example usage: get_edge_array(node_count, node_start) and returns: np