code: def build_model(cls, args: argparse.Namespace) -> ESPnetSpeakerModel:
      assert check_argument_types()
  
      if args.frontend is not None:
          frontend_class = frontend_choices.get_class(args.frontend)
          frontend = frontend_class(**args.frontend_conf)
          input_size = frontend.output_size()
      else:
          # Give features from data-loader (e.g., precompute features).
          frontend = None
          input_size = args.input_size
  
      if args.specaug is not None:
          specaug_class = specaug_choices.get_class(args.specaug)
          specaug = specaug_class(**args.specaug_conf)
      else:
          specaug = None
  
      if args.normalize is not None:
          normalize_class = normalize_choices.get_class(args.normalize)
          normalize = normalize_class(**args.normalize_conf)
      else:
          normalize = None
  
      encoder_class = encoder_choices.get_class(args.encoder)
      encoder = encoder_class(
          input_size=input_size, **args.encoder_conf
      )
      encoder_output_size = encoder.output_size()
  
      pooling_class = pooling_choices.get_class(args.pooling)
      pooling = pooling_class(
          input_size=encoder_output_size, **args.pooling_conf
      )
      pooling_output_size = pooling.output_size()
  
      projector_class = projector_choices.get_class(args.projector)
      projector = projector_class(
          input_size=pooling_output_size, **args.projector_conf
      )
      projector_output_size = projector.output_size()
  
      loss_class = loss_choices.get_class(args.loss)
      loss = loss_class(
          nout=projector_output_size,
          nclasses=args.spk_num,
          **args.loss_conf,
      )
  
      model = ESPnetSpeakerModel(
          frontend=frontend,
          specaug=specaug,
          normalize=normalize,
          encoder=encoder,
          pooling=pooling,
          projector=projector,
          loss=loss,
          # **args.model_conf, # uncomment when model_conf exists
      )
  
      if args.init is not None:
          initialize(model, args.init)
  
      assert check_return_type(model)
      return model
  
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 6 for calling the SpeakerTask obj's underlying member method code with example usage: obj.build_model(cls, args) and returns: model