code: def main():
      arg_parser = argparse.ArgumentParser()
      arg_parser.add_argument(
          "--host",
          type=str,
          default=defaults.host,
          help="hostname the server should use, default is "
          f"{defaults.host}",
      )
      arg_parser.add_argument(
          "--port",
          type=int,
          default=defaults.port,
          help="port the server should listen on, default "
          f"is {defaults.port}",
      )
      arg_parser.add_argument(
          "--graph-creation-extension-dir",
          type=Path,
          help="dir to load graph creation extension " "functions from",
      )
      arg_parser.add_argument(
          "--dask-scheduler-file",
          type=Path,
          help="file generated by a dask scheduler, used "
          "for connecting to a dask cluster for MG support",
      )
      arg_parser.add_argument(
          "--start-local-cuda-cluster",
          action="store_true",
          help="use a LocalCUDACluster for multi-GPU",
      )
      arg_parser.add_argument(
          "--protocol",
          type=str,
          help="protocol to use by the dask cluster, ex 'ucx'",
      )
      arg_parser.add_argument(
          "--rmm-pool-size",
          type=str,
          help="RMM pool size, ex. '28GB'",
      )
      arg_parser.add_argument(
          "--dask-worker-devices",
          type=str,
          help="list of GPU device IDs the dask cluster should use, ex. '0,1,2,3'",
      )
      args = arg_parser.parse_args()
  
      msg = "Starting the cugraph_service server "
      if (args.dask_scheduler_file is None) and (
          args.start_local_cuda_cluster is False
      ):
          msg += "(single-GPU)..."
      elif (args.dask_scheduler_file is not None) and (
          args.start_local_cuda_cluster is True
      ):
          raise RuntimeError(
              "dask-scheduler-file cannot be set if start-local-cuda-cluster is specified"
          )
      elif args.dask_scheduler_file is not None:
          msg += f"(multi-GPU, scheduler file: {args.dask_scheduler_file})..."
      elif args.start_local_cuda_cluster is True:
          msg += "(multi-GPU, LocalCUDACluster)..."
  
      start_server_blocking(
          args.graph_creation_extension_dir,
          args.start_local_cuda_cluster,
          args.dask_scheduler_file,
          args.host,
          args.port,
          args.protocol,
          args.rmm_pool_size,
          args.dask_worker_devices,
          console_message=msg,
      )
      print("done.")
  
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types