code: def bench_hits(benchmark, graph_obj, backend_wrapper, normalized):
      G = get_graph_obj_for_benchmark(graph_obj, backend_wrapper)
      result = benchmark.pedantic(
          target=backend_wrapper(nx.hits),
          args=(G,),
          kwargs=dict(
              normalized=normalized,
          ),
          rounds=rounds,
          iterations=iterations,
          warmup_rounds=warmup_rounds,
      )
      assert type(result) is tuple
      assert len(result) == 2
      assert type(result[0]) is dict
      assert type(result[1]) is dict
  
imports: import random
  import networkx
  import pandas
  import pytest
  from cugraph import datasets
  import nx_cugraph
label_desc: Use image node_id 14 for calling a global function with example usage: bench_hits(benchmark, graph_obj, backend_wrapper, normalized) without return types