code: def get_parser():
      parser = config_argparse.ArgumentParser(
          description="Speaker Diarization inference",
          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("--output_dir", type=str, required=True)
      parser.add_argument(
          "--ngpu",
          type=int,
          default=0,
          help="The number of gpus. 0 indicates CPU mode",
      )
      parser.add_argument(
          "--seed", type=int, default=0, help="Random seed"
      )
      parser.add_argument(
          "--dtype",
          default="float32",
          choices=["float16", "float32", "float64"],
          help="Data type",
      )
      parser.add_argument(
          "--fs",
          type=humanfriendly_parse_size_or_none,
          default=8000,
          help="Sampling rate",
      )
      parser.add_argument(
          "--num_workers",
          type=int,
          default=1,
          help="The number of workers used for DataLoader",
      )
  
      group = parser.add_argument_group("Input data related")
      group.add_argument(
          "--data_path_and_name_and_type",
          type=str2triple_str,
          required=True,
          action="append",
      )
      group.add_argument("--key_file", type=str_or_none)
      group.add_argument(
          "--allow_variable_data_keys", type=str2bool, default=False
      )
  
      group = parser.add_argument_group(
          "The model configuration related"
      )
      group.add_argument(
          "--train_config",
          type=str,
          help="Diarization training configuration",
      )
      group.add_argument(
          "--model_file",
          type=str,
          help="Diarization model parameter file",
      )
      group.add_argument(
          "--model_tag",
          type=str,
          help="Pretrained model tag. If specify this option, train_config and "
          "model_file will be overwritten",
      )
  
      group = parser.add_argument_group("Data loading related")
      group.add_argument(
          "--batch_size",
          type=int,
          default=1,
          help="The batch size for inference",
      )
      group = parser.add_argument_group("Diarize speech related")
      group.add_argument(
          "--segment_size",
          type=float,
          default=None,
          help="Segment length in seconds for segment-wise speaker diarization",
      )
      group.add_argument(
          "--hop_size",
          type=float,
          default=None,
          help="Hop length in seconds for segment-wise speech enhancement/separation",
      )
      group.add_argument(
          "--show_progressbar",
          type=str2bool,
          default=False,
          help="Whether to show a progress bar when performing segment-wise speaker "
          "diarization",
      )
      group.add_argument(
          "--num_spk",
          type=int_or_none,
          default=None,
          help="Predetermined number of speakers for inference",
      )
  
      group = parser.add_argument_group("Enh + Diar related")
      group.add_argument(
          "--enh_s2t_task",
          type=str2bool,
          default=False,
          help="enhancement and diarization joint model",
      )
      group.add_argument(
          "--normalize_segment_scale",
          type=str2bool,
          default=False,
          help="Whether to normalize the energy of the separated streams in each segment",
      )
      group.add_argument(
          "--normalize_output_wav",
          type=str2bool,
          default=False,
          help="Whether to normalize the predicted wav to [-1~1]",
      )
      group.add_argument(
          "--multiply_diar_result",
          type=str2bool,
          default=False,
          help="Whether to multiply diar results to separated waves",
      )
  
      return parser
  
imports: import argparse
  import logging
  import sys
  from itertools import permutations
  from pathlib import Path
  from typing import Any, List, Optional, Sequence, Tuple, Union
  import numpy
  import torch
  import torch.nn.functional
  from tqdm import trange
  from typeguard import check_argument_types
  from espnet2.enh.loss.criterions.tf_domain import FrequencyDomainMSE
  from espnet2.enh.loss.criterions.time_domain import SISNRLoss
  from espnet2.enh.loss.wrappers.pit_solver import PITSolver
  from espnet2.fileio.npy_scp import NpyScpWriter
  from espnet2.fileio.sound_scp import SoundScpWriter
  from espnet2.tasks.diar import DiarizationTask
  from espnet2.tasks.enh_s2t import EnhS2TTask
  from espnet2.torch_utils.device_funcs import to_device
  from espnet2.torch_utils.set_all_random_seed import set_all_random_seed
  from espnet2.utils import config_argparse
  from espnet2.utils.types import humanfriendly_parse_size_or_none, int_or_none, str2bool, str2triple_str, 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