code: def parameters_option(
      step_num, model, ckpt_dir, option="Saving", ctx_l=None
  ):
      """Save or load the model parameter, marked by step_num."""
      param_path = os.path.join(
          ckpt_dir, "{}.params".format(str(step_num).zfill(7))
      )
      logging.info(
          "[step {}], {} model params to/from {}.".format(
              step_num, option, param_path
          )
      )
      if option == "Saving":
          model.save_parameters(param_path)
      elif option == "Loading":
          model.load_parameters(param_path, ctx=ctx_l)
      else:
          raise NotImplementedError("Unknown Option: {}".format(option))
  
file_path: gluon-nlp/scripts/pretraining/bert/run_pretraining.py
imports: import os
  import time
  import shutil
  import logging
  import argparse
  import functools
  import collections
  import mxnet
  import numpy
  from pretraining_utils import get_pretrain_data_npz, get_pretrain_data_text, MaskedAccuracy
  from gluonnlp.utils.misc import repeat, grouper, set_seed, init_comm, logging_config, naming_convention
  from gluonnlp.initializer import TruncNorm
  from gluonnlp.models.bert import BertModel, BertForPretrain, get_pretrained_bert
  from gluonnlp.utils.parameter import clip_grad_global_norm
label_desc: Use image node_id 4 for calling a global function with example usage: parameters_option(step_num, model, ckpt_dir, option, ctx_l) without return types