code: def betweenness_centrality(
      G,
      k=None,
      normalized=True,
      weight=None,
      endpoints=False,
      seed=None,
  ):
      """`weight` parameter is not yet supported, and RNG with seed may be different."""
      if weight is not None:
          raise NotImplementedError(
              "Weighted implementation of betweenness centrality not currently supported"
          )
      seed = _seed_to_int(seed)
      G = _to_graph(G, weight)
      node_ids, values = plc.betweenness_centrality(
          resource_handle=plc.ResourceHandle(),
          graph=G._get_plc_graph(),
          k=k,
          random_state=seed,
          normalized=normalized,
          include_endpoints=endpoints,
          do_expensive_check=False,
      )
      return G._nodearrays_to_dict(node_ids, values)
  
imports: import pylibcugraph
  from nx_cugraph.convert import _to_graph
  from nx_cugraph.utils import _seed_to_int, networkx_algorithm
label_desc: Use image node_id 1 for calling a global function with example usage: betweenness_centrality(G, k, normalized, weight, endpoints, seed) and returns: G