code: def get_parser():
      """Get default arguments."""
      parser = configargparse.ArgumentParser(
          description="Translate text from speech "
          "using a speech translation model on one CPU or GPU",
          config_file_parser_class=configargparse.YAMLConfigFileParser,
          formatter_class=configargparse.ArgumentDefaultsHelpFormatter,
      )
      # general configuration
      parser.add(
          "--config", is_config_file=True, help="Config file path"
      )
      parser.add(
          "--config2",
          is_config_file=True,
          help="Second config file path that overwrites the settings in `--config`",
      )
      parser.add(
          "--config3",
          is_config_file=True,
          help="Third config file path "
          "that overwrites the settings in `--config` and `--config2`",
      )
  
      parser.add_argument(
          "--ngpu", type=int, default=0, help="Number of GPUs"
      )
      parser.add_argument(
          "--dtype",
          choices=("float16", "float32", "float64"),
          default="float32",
          help="Float precision (only available in --api v2)",
      )
      parser.add_argument(
          "--backend",
          type=str,
          default="chainer",
          choices=["chainer", "pytorch"],
          help="Backend library",
      )
      parser.add_argument(
          "--debugmode", type=int, default=1, help="Debugmode"
      )
      parser.add_argument(
          "--seed", type=int, default=1, help="Random seed"
      )
      parser.add_argument(
          "--verbose", "-V", type=int, default=1, help="Verbose option"
      )
      parser.add_argument(
          "--batchsize",
          type=int,
          default=1,
          help="Batch size for beam search (0: means no batch processing)",
      )
      parser.add_argument(
          "--preprocess-conf",
          type=str,
          default=None,
          help="The configuration file for the pre-processing",
      )
      parser.add_argument(
          "--api",
          default="v1",
          choices=["v1", "v2"],
          help="Beam search APIs "
          "v1: Default API. It only supports "
          "the ASRInterface.recognize method and DefaultRNNLM. "
          "v2: Experimental API. "
          "It supports any models that implements ScorerInterface.",
      )
      # task related
      parser.add_argument(
          "--trans-json",
          type=str,
          help="Filename of translation data (json)",
      )
      parser.add_argument(
          "--result-label",
          type=str,
          required=True,
          help="Filename of result label data (json)",
      )
      # model (parameter) related
      parser.add_argument(
          "--model",
          type=str,
          required=True,
          help="Model file parameters to read",
      )
      parser.add_argument(
          "--model-conf",
          type=str,
          default=None,
          help="Model config file",
      )
      # search related
      parser.add_argument(
          "--nbest",
          type=int,
          default=1,
          help="Output N-best hypotheses",
      )
      parser.add_argument(
          "--beam-size", type=int, default=1, help="Beam size"
      )
      parser.add_argument(
          "--penalty", type=float, default=0.1, help="Incertion penalty"
      )
      parser.add_argument(
          "--maxlenratio",
          type=float,
          default=3.0,
          help="""Input length ratio to obtain max output length.
                          If maxlenratio=0.0 (default), it uses a end-detect function
                          to automatically find maximum hypothesis lengths""",
      )
      parser.add_argument(
          "--minlenratio",
          type=float,
          default=0.0,
          help="Input length ratio to obtain min output length",
      )
      # multilingual related
      parser.add_argument(
          "--tgt-lang",
          default=False,
          type=str,
          help="target language ID (e.g., <en>, <de>, and <fr> etc.)",
      )
      return parser
  
imports: import logging
  import os
  import random
  import sys
  import configargparse
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: get_parser() and returns: parser