code: def test_local_feature_store_utils():
      store = LocalFeatureStore()
  
      feat = torch.tensor(
          [
              [0.0, 0.0, 0.0],
              [1.0, 1.0, 1.0],
              [2.0, 2.0, 2.0],
              [3.0, 3.0, 3.0],
              [4.0, 4.0, 4.0],
              [5.0, 5.0, 5.0],
              [6.0, 6.0, 6.0],
              [7.0, 7.0, 7.0],
              [8.0, 8.0, 8.0],
          ]
      )
  
      paper_global_id = torch.tensor([1, 2, 3, 5, 8, 4])
      paper_feat = feat[paper_global_id]
  
      store.put_tensor(paper_feat, group_name="paper", attr_name="feat")
  
      assert len(store.get_all_tensor_attrs()) == 1
      attr = store.get_all_tensor_attrs()[0]
      assert attr.group_name == "paper"
      assert attr.attr_name == "feat"
      assert attr.index is None
      assert store.get_tensor_size(attr) == (6, 3)
  
imports: import torch
  from torch_geometric.distributed import LocalFeatureStore
label_desc: Use image node_id 2 for calling a global function with example usage: test_local_feature_store_utils() without return types