code: def test_homogeneous_graph_store():
      edge_id = torch.randperm(300)
      edge_index = get_random_edge_index(100, 100, 300)
      edge_index[1] = torch.sort(edge_index[1])[0]
  
      graph_store = LocalGraphStore.from_data(
          edge_id,
          edge_index,
          num_nodes=100,
          is_sorted=True,
      )
  
      assert len(graph_store.get_all_edge_attrs()) == 1
      edge_attr = graph_store.get_all_edge_attrs()[0]
      assert edge_attr.edge_type is None
      assert edge_attr.layout.value == "coo"
      assert edge_attr.is_sorted
      assert edge_attr.size == (100, 100)
  
      assert torch.equal(
          graph_store.get_edge_id(edge_type=None, layout="coo"),
          edge_id,
      )
      assert torch.equal(
          graph_store.get_edge_index(edge_type=None, layout="coo"),
          edge_index,
      )
  
imports: import torch
  from torch_geometric.distributed import LocalGraphStore
  from torch_geometric.testing import get_random_edge_index
label_desc: Use image node_id 2 for calling a global function with example usage: test_homogeneous_graph_store() without return types