code: def build_model(cls, args: argparse.Namespace) -> ESPnetLanguageModel:
      assert check_argument_types()
      if isinstance(args.token_list, str):
          with open(args.token_list, encoding="utf-8") as f:
              token_list = [line.rstrip() for line in f]
  
          # "args" is saved as it is in a yaml file by BaseTask.main().
          # Overwriting token_list to keep it as "portable".
          args.token_list = token_list.copy()
      elif isinstance(args.token_list, (tuple, list)):
          token_list = args.token_list.copy()
      else:
          raise RuntimeError("token_list must be str or dict")
  
      vocab_size = len(token_list)
      logging.info(f"Vocabulary size: {vocab_size }")
  
      # 1. Build LM model
      lm_class = lm_choices.get_class(args.lm)
      lm = lm_class(vocab_size=vocab_size, **args.lm_conf)
  
      # 2. Build ESPnetModel
      # Assume the last-id is sos_and_eos
      model = ESPnetLanguageModel(
          lm=lm, vocab_size=vocab_size, **args.model_conf
      )
  
      # FIXME(kamo): Should be done in model?
      # 3. Initialize
      if args.init is not None:
          initialize(model, args.init)
  
      assert check_return_type(model)
      return model
  
imports: import argparse
  import logging
  from typing import Callable, Collection, Dict, List, Optional, Tuple
  import numpy
  import torch
  from typeguard import check_argument_types, check_return_type
  from espnet2.lm.abs_model import AbsLM
  from espnet2.lm.espnet_model import ESPnetLanguageModel
  from espnet2.lm.seq_rnn_lm import SequentialRNNLM
  from espnet2.lm.transformer_lm import TransformerLM
  from espnet2.tasks.abs_task import AbsTask
  from espnet2.text.phoneme_tokenizer import g2p_choices
  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 CommonPreprocessor
  from espnet2.train.trainer import Trainer
  from espnet2.utils.get_default_kwargs import get_default_kwargs
  from espnet2.utils.nested_dict_action import NestedDictAction
  from espnet2.utils.types import str2bool, str_or_none
label_desc: Use image node_id 6 for calling the LMTask obj's underlying member method code with example usage: obj.build_model(cls, args) and returns: model