code: def parse_args():
      parser = argparse.ArgumentParser(description=__doc__)
      group = parser.add_mutually_exclusive_group(required=True)
      group.add_argument(
          "--model-name",
          type=str,
          default="google_electra_small",
          help="Name of the pretrained model.",
      )
      parser.add_argument(
          "--params-file",
          type=str,
          required=True,
          help="Path to the pretrained parameter file.",
      )
      parser.add_argument(
          "--out-file", type=str, default=None, help="Output file path."
      )
      parser.add_argument(
          "--generator_units_scale",
          type=float,
          default=None,
          help="The scale size of the generator units, same as used in pretraining.",
      )
      parser.add_argument(
          "--generator_layers_scale",
          type=float,
          default=None,
          help="The scale size of the generator layer, same as used in pretraining.",
      )
  
      args = parser.parse_args()
      return args
  
imports: import os
  import argparse
  import mxnet
  from pretraining_utils import get_electra_pretraining_model
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args