code: def bench_k_truss(benchmark, graph_obj, backend_wrapper):
      G = get_graph_obj_for_benchmark(graph_obj, backend_wrapper)
      # DiGraphs are not supported
      if G.is_directed():
          G = G.to_undirected()
      result = benchmark.pedantic(
          target=backend_wrapper(nx.k_truss),
          args=(G,),
          kwargs=dict(
              k=2,
          ),
          rounds=rounds,
          iterations=iterations,
          warmup_rounds=warmup_rounds,
      )
      # Check that this at least appears to be some kind of NX-like Graph
      assert hasattr(result, "has_node")
  
imports: import random
  import networkx
  import pandas
  import pytest
  from cugraph import datasets
  import nx_cugraph
label_desc: Use image node_id 17 for calling a global function with example usage: bench_k_truss(benchmark, graph_obj, backend_wrapper) without return types