code: def parse_args():
      parser = argparse.ArgumentParser(
          description="Convert the TF pretrained model to Gluon"
      )
      parser.add_argument(
          "--tf_hub_model_path",
          type=str,
          required=True,
          help="Directory of the model downloaded from TF hub.",
      )
      parser.add_argument(
          "--model_type",
          type=str,
          choices=["bert", "albert"],
          help="The name of the model to be converted. "
          "Only Bert and Albert are currently supported.",
      )
      parser.add_argument(
          "--save_dir",
          type=str,
          default=None,
          help="directory path to save the converted pretrained model.",
      )
      parser.add_argument("--test", action="store_true")
      parser.add_argument("--torch", action="store_true")
      parser.add_argument(
          "--cuda",
          action=BooleanOptionalAction,
          default=True,
          help="Use Cuda if available.",
      )
      args = parser.parse_args()
  
      if args.torch:
          if th.cuda.is_available() and args.cuda:
              args.device = th.device("cuda", 0)
          else:
              args.device = th.device("cpu")
      else:
          args.ctx = mx.gpu() if args.cuda else mx.cpu()
  
      return args
  
imports: import tensorflow_hub
  import tensorflow.compat.v1
  import os
  import re
  import json
  import shutil
  import logging
  import argparse
  import mxnet
  import torch
  import numpy
  from numpy.testing import assert_allclose
  from gluonnlp.data.vocab import Vocab
  from gluonnlp.utils.misc import naming_convention, logging_config, BooleanOptionalAction
  from gluonnlp.models.bert import BertModel, BertForMLM
  from gluonnlp.models.albert import AlbertModel, AlbertForMLM
  from gluonnlp.torch.models.bert import BertModel, BertForMLM
  from gluonnlp.data.tokenizers import SentencepieceTokenizer, HuggingFaceWordPieceTokenizer
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args