code: def parse_args():
      parser = argparse.ArgumentParser(
          "Convert Huggingface mT5 Model to GluonNLP"
      )
      parser.add_argument(
          "model_name",
          choices=list(MT5_PRETRAINED_MODEL_MAP.keys()),
          help="Name of pretrained T5 model in Huggingface.",
      )
      parser.add_argument(
          "dest_dir",
          help="Directory to save converted config, vocab and weights.",
      )
      parser.add_argument(
          "--test",
          action="store_true",
          required=False,
          default=False,
          help="Whether to test conversion correctness.",
      )
      args = parser.parse_args()
      # further process mappings
      args.tgt_model_name = MT5_PRETRAINED_MODEL_MAP[args.model_name]
      args.config_url = MT5_PRETRAINED_CONFIG_MAP[args.model_name]
      args.vocab_url = MT5_PRETRAINED_VOCAB_MAP[args.model_name]
      return args
  
file_path: gluon-nlp/docs/model_zoo/conversion_toolkits/convert_mt5.py
imports: import argparse
  import logging
  import os
  from gluonnlp.utils.misc import logging_config, sha1sum
  from gluonnlp.models.mt5 import MT5Model
  from transformers import MT5Model
  from convert_t5 import parse_args, convert_config, convert_vocab, convert_params, rename, test_conversion
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args