code: def parse_args():
      parser = ArgumentParser()
      parser.add_argument(
          "--model-type",
          type=str,
          choices=[
              MODEL_TYPE_LIBRISPEECH,
              MODEL_TYPE_TEDLIUM3,
              MODEL_TYPE_MUSTC,
          ],
          required=True,
      )
      parser.add_argument(
          "--global-stats-path",
          default=pathlib.Path("global_stats.json"),
          type=pathlib.Path,
          help="Path to JSON file containing feature means and stddevs.",
          required=True,
      )
      parser.add_argument(
          "--dataset-path",
          type=pathlib.Path,
          help="Path to datasets.",
          required=True,
      )
      parser.add_argument(
          "--sp-model-path",
          type=pathlib.Path,
          help="Path to SentencePiece model.",
          required=True,
      )
      parser.add_argument(
          "--exp-dir",
          default=pathlib.Path("./exp"),
          type=pathlib.Path,
          help="Directory to save checkpoints and logs to. (Default: './exp')",
      )
      parser.add_argument(
          "--num-nodes",
          default=4,
          type=int,
          help="Number of nodes to use for training. (Default: 4)",
      )
      parser.add_argument(
          "--gpus",
          default=8,
          type=int,
          help="Number of GPUs per node to use for training. (Default: 8)",
      )
      parser.add_argument(
          "--epochs",
          default=120,
          type=int,
          help="Number of epochs to train for. (Default: 120)",
      )
      parser.add_argument(
          "--gradient-clip-val",
          default=10.0,
          type=float,
          help="Value to clip gradient values to. (Default: 10.0)",
      )
      parser.add_argument(
          "--debug",
          action="store_true",
          help="whether to use debug level for logging",
      )
      return parser.parse_args()
  
file_path: audio/examples/asr/emformer_rnnt/train.py
imports: import logging
  import pathlib
  from argparse import ArgumentParser
  from common import MODEL_TYPE_LIBRISPEECH, MODEL_TYPE_MUSTC, MODEL_TYPE_TEDLIUM3
  from librispeech.lightning import LibriSpeechRNNTModule
  from mustc.lightning import MuSTCRNNTModule
  from pytorch_lightning import Trainer
  from pytorch_lightning.callbacks import ModelCheckpoint
  from tedlium3.lightning import TEDLIUM3RNNTModule
label_desc: Use image node_id 3 for calling a global function with example usage: parse_args() and returns: parser