code: def add_task_arguments(cls, parser: argparse.ArgumentParser):
      group = parser.add_argument_group(description="Task related")
  
      group.add_argument(
          "--init",
          type=lambda x: str_or_none(x.lower()),
          default=None,
          help="The initialization method",
          choices=[
              "chainer",
              "xavier_uniform",
              "xavier_normal",
              "kaiming_uniform",
              "kaiming_normal",
              None,
          ],
      )
  
      group.add_argument(
          "--use_preprocessor",
          type=str2bool,
          default=True,
          help="Apply preprocessing to data or not",
      )
  
      group.add_argument(
          "--input_size",
          type=int_or_none,
          default=None,
          help="The number of input dimension of the feature",
      )
  
      group.add_argument(
          "--target_duration",
          type=float,
          default=3.0,
          help="Duration (in seconds) of samples in a minibatch",
      )
  
      group.add_argument(
          "--spk2utt",
          type=str,
          default="",
          help="Directory of spk2utt file to be used in label mapping",
      )
  
      group.add_argument(
          "--spk_num",
          type=int,
          default=None,
          help="specify the number of speakers during training",
      )
  
      group.add_argument(
          "--sample_rate",
          type=int,
          default=16000,
          help="Sampling rate",
      )
  
      group.add_argument(
          "--num_eval",
          type=int,
          default=10,
          help="Number of segments to make from one utterance in the "
          "inference phase",
      )
  
      group.add_argument(
          "--rir_scp",
          type=str,
          default="",
          help="Directory of the rir data to be augmented",
      )
  
      group.add_argument(
          "--model_conf",
          action=NestedDictAction,
          default=get_default_kwargs(ESPnetSpeakerModel),
          help="The keyword arguments for model class.",
      )
  
      for class_choices in cls.class_choices_list:
          class_choices.add_arguments(group)
  
imports: import argparse
  from typing import Callable, Collection, Dict, List, Optional, Tuple
  import numpy
  import torch
  from typeguard import check_argument_types, check_return_type
  from espnet2.asr.encoder.abs_encoder import AbsEncoder
  from espnet2.asr.frontend.abs_frontend import AbsFrontend
  from espnet2.asr.frontend.asteroid_frontend import AsteroidFrontend
  from espnet2.asr.frontend.default import DefaultFrontend
  from espnet2.asr.frontend.fused import FusedFrontends
  from espnet2.asr.frontend.melspec_torch import MelSpectrogramTorch
  from espnet2.asr.frontend.s3prl import S3prlFrontend
  from espnet2.asr.frontend.windowing import SlidingWindow
  from espnet2.asr.specaug.abs_specaug import AbsSpecAug
  from espnet2.asr.specaug.specaug import SpecAug
  from espnet2.layers.abs_normalize import AbsNormalize
  from espnet2.layers.global_mvn import GlobalMVN
  from espnet2.layers.utterance_mvn import UtteranceMVN
  from espnet2.spk.encoder.ecapa_tdnn_encoder import EcapaTdnnEncoder
  from espnet2.spk.encoder.rawnet3_encoder import RawNet3Encoder
  from espnet2.spk.espnet_model import ESPnetSpeakerModel
  from espnet2.spk.loss.aamsoftmax import AAMSoftmax
  from espnet2.spk.loss.aamsoftmax_subcenter_intertopk import ArcMarginProduct_intertopk_subcenter
  from espnet2.spk.loss.abs_loss import AbsLoss
  from espnet2.spk.pooling.abs_pooling import AbsPooling
  from espnet2.spk.pooling.chn_attn_stat_pooling import ChnAttnStatPooling
  from espnet2.spk.projector.abs_projector import AbsProjector
  from espnet2.spk.projector.rawnet3_projector import RawNet3Projector
  from espnet2.tasks.abs_task import AbsTask
  from espnet2.torch_utils.initialize import initialize
  from espnet2.train.class_choices import ClassChoices
  from espnet2.train.collate_fn import CommonCollateFn
  from espnet2.train.preprocessor import AbsPreprocessor, CommonPreprocessor, SpkPreprocessor
  from espnet2.train.spk_trainer import SpkTrainer
  from espnet2.utils.get_default_kwargs import get_default_kwargs
  from espnet2.utils.nested_dict_action import NestedDictAction
  from espnet2.utils.types import int_or_none, str2bool, str_or_none
label_desc: Use image node_id 1 for calling the SpeakerTask obj's underlying member method code with example usage: obj.add_task_arguments(cls, parser) without return types