code: def triangle_count(input_graph, start_list=None):
      """
      Computes the number of triangles (cycles of length three) and the number
      per vertex in the input graph.
  
      Parameters
      ----------
      input_graph : cugraph.graph
          cuGraph graph descriptor, should contain the connectivity information,
          (edge weights are not used in this algorithm).
          The current implementation only supports undirected graphs.
  
      start_list : list or cudf.Series
          list of vertices for triangle count. if None the entire set of vertices
          in the graph is processed
  
  
      Returns
      -------
      result : dask_cudf.DataFrame
          GPU distributed data frame containing 2 dask_cudf.Series
  
      ddf['vertex']: dask_cudf.Series
              Contains the triangle counting vertices
      ddf['counts']: dask_cudf.Series
          Contains the triangle counting counts
      """
      if input_graph.is_directed():
          raise ValueError("input graph must be undirected")
      # Initialize dask client
      client = default_client()
  
      if start_list is not None:
          if isinstance(start_list, int):
              start_list = [start_list]
          if isinstance(start_list, list):
              start_list = cudf.Series(start_list)
          if not isinstance(start_list, cudf.Series):
              raise TypeError(
                  f"'start_list' must be either a list or a cudf.Series,"
                  f"got: {start_list.dtype}"
              )
  
          # start_list uses "external" vertex IDs, but since the graph has been
          # renumbered, the start vertex IDs must also be renumbered.
          if input_graph.renumbered:
              start_list = input_graph.lookup_internal_vertex_id(
                  start_list
              ).compute()
  
      do_expensive_check = False
  
      result = [
          client.submit(
              _call_triangle_count,
              Comms.get_session_id(),
              input_graph._plc_graph[w],
              start_list,
              do_expensive_check,
              workers=[w],
              allow_other_workers=False,
          )
          for w in Comms.get_workers()
      ]
      wait(result)
  
      cudf_result = [
          client.submit(convert_to_cudf, cp_arrays)
          for cp_arrays in result
      ]
  
      wait(cudf_result)
  
      ddf = dask_cudf.from_delayed(cudf_result).persist()
      wait(ddf)
      # Wait until the inactive futures are released
      wait(
          [
              (r.release(), c_r.release())
              for r, c_r in zip(result, cudf_result)
          ]
      )
  
      if input_graph.renumbered:
          ddf = input_graph.unrenumber(ddf, "vertex")
  
      return ddf
  
imports: from dask.distributed import wait, default_client
  import cugraph.dask.comms.comms
  import dask_cudf
  import cudf
  from pylibcugraph import ResourceHandle, triangle_count
label_desc: Use image node_id 3 for calling a global function with example usage: triangle_count(input_graph, start_list) and returns: ddf