code: def get_parser():
      """Obtain an argument-parser for the script interface."""
      parser = config_argparse.ArgumentParser(
          description="ASR Decoding",
          formatter_class=argparse.ArgumentDefaultsHelpFormatter,
      )
  
      # Note(kamo): Use '_' instead of '-' as separator.
      # '-' is confusing if written in yaml.
      parser.add_argument(
          "--log_level",
          type=lambda x: x.upper(),
          default="INFO",
          choices=(
              "CRITICAL",
              "ERROR",
              "WARNING",
              "INFO",
              "DEBUG",
              "NOTSET",
          ),
          help="The verbose level of logging",
      )
  
      parser.add_argument(
          "--ngpu",
          type=int,
          default=0,
          help="The number of gpus. 0 indicates CPU mode",
      )
      parser.add_argument(
          "--dtype",
          default="float32",
          choices=["float16", "float32", "float64"],
          help="Data type",
      )
  
      group = parser.add_argument_group("Model configuration related")
      group.add_argument("--asr_train_config", type=str, required=True)
      group.add_argument("--asr_model_file", type=str, required=True)
  
      group = parser.add_argument_group("Text converter related")
      group.add_argument(
          "--token_type",
          type=str_or_none,
          default=None,
          choices=["char", "bpe", None],
          help="The token type for ASR model. "
          "If not given, refers from the training args",
      )
      group.add_argument(
          "--bpemodel",
          type=str_or_none,
          default=None,
          help="The model path of sentencepiece. "
          "If not given, refers from the training args",
      )
  
      group = parser.add_argument_group("CTC segmentation related")
      group.add_argument(
          "--fs",
          type=int,
          default=16000,
          help="Sampling Frequency."
          " The sampling frequency (in Hz) is needed to correctly determine the"
          " starting and ending time of aligned segments.",
      )
      group.add_argument(
          "--min_window_size",
          type=int,
          default=None,
          help="Minimum window size considered for utterance.",
      )
      group.add_argument(
          "--max_window_size",
          type=int,
          default=None,
          help="Maximum window size considered for utterance.",
      )
      group.add_argument(
          "--set_blank",
          type=int,
          default=None,
          help="Index of model dictionary for blank token.",
      )
      group.add_argument(
          "--gratis_blank",
          type=str2bool,
          default=False,
          help="Set the transition cost of the blank token to zero. Audio sections"
          " labeled with blank tokens can then be skipped without penalty. Useful"
          " if there are unrelated audio segments between utterances.",
      )
      group.add_argument(
          "--replace_spaces_with_blanks",
          type=str2bool,
          default=False,
          help="Fill blanks in between words to better model pauses between words."
          " This option is only active for `--text_converter classic`."
          " Segments can be misaligned if this option is combined with"
          " --gratis-blank.",
      )
      group.add_argument(
          "--scoring_length",
          type=int,
          default=None,
          help="Changes partitioning length L for calculation of the confidence score.",
      )
      group.add_argument(
          "--time_stamps",
          type=str,
          default=CTCSegmentation.time_stamps,
          choices=CTCSegmentation.choices_time_stamps,
          help="Select method how CTC index duration is estimated, and"
          " thus how the time stamps are calculated.",
      )
      group.add_argument(
          "--text_converter",
          type=str,
          default=CTCSegmentation.text_converter,
          choices=CTCSegmentation.choices_text_converter,
          help="How CTC segmentation handles text.",
      )
  
      group = parser.add_argument_group("Input/output arguments")
      group.add_argument(
          "--kaldi_style_text",
          type=str2bool,
          default=True,
          help="Assume that the input text file is kaldi-style formatted, i.e., the"
          " utterance name is at the beginning of each line.",
      )
      group.add_argument(
          "--print_utt_text",
          type=str2bool,
          default=True,
          help="Include the utterance text in the segments output.",
      )
      group.add_argument(
          "--print_utt_score",
          type=str2bool,
          default=True,
          help="Include the confidence score in the segments output.",
      )
      group.add_argument(
          "-a",
          "--audio",
          type=Path,
          required=True,
          help="Input audio file.",
      )
      group.add_argument(
          "-t",
          "--text",
          type=argparse.FileType("r"),
          required=True,
          help="Input text file."
          " Each line contains the ground truth of a single utterance."
          " Kaldi-style text files include the name of the utterance as"
          " the first word in the line.",
      )
      group.add_argument(
          "-o",
          "--output",
          type=argparse.FileType("w"),
          default="-",
          help="Output in the form of a `segments` file."
          " If not given, output is written to stdout.",
      )
      return parser
  
imports: import argparse
  import logging
  import sys
  from pathlib import Path
  from typing import List, Optional, TextIO, Union
  import numpy
  import soundfile
  import torch
  from ctc_segmentation import CtcSegmentationParameters, ctc_segmentation, determine_utterance_segments, prepare_text, prepare_token_list
  from typeguard import check_argument_types, check_return_type
  from espnet2.tasks.asr import ASRTask
  from espnet2.torch_utils.device_funcs import to_device
  from espnet2.utils import config_argparse
  from espnet2.utils.types import str2bool, str_or_none
  from espnet.utils.cli_utils import get_commandline_args
label_desc: Use image node_id 2 for calling a global function with example usage: get_parser() and returns: parser