code: def pre_process(dataset, prog_args):
      """
      diffpool specific data partition, pre-process and shuffling
      """
      if prog_args.data_mode != "default":
          print(
              "overwrite node attributes with DiffPool's preprocess setting"
          )
          if prog_args.data_mode == "id":
              for g, _ in dataset:
                  id_list = np.arange(g.num_nodes())
                  g.ndata["feat"] = one_hotify(
                      id_list, pad=dataset.max_num_node
                  )
  
          elif prog_args.data_mode == "deg-num":
              for g, _ in dataset:
                  g.ndata["feat"] = np.expand_dims(
                      g.in_degrees(), axis=1
                  )
  
          elif prog_args.data_mode == "deg":
              for g in dataset:
                  degs = list(g.in_degrees())
                  degs_one_hot = one_hotify(
                      degs, pad=dataset.max_degrees
                  )
                  g.ndata["feat"] = degs_one_hot
  
label_desc: Use image node_id 2 for calling a global function with example usage: pre_process(dataset, prog_args) without return types