code: def required_data_names(
      cls, train: bool = True, inference: bool = False
  ) -> Tuple[str, ...]:
      retval = ("text",)
      return retval
  
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 4 for calling the LMTask obj's underlying member method code with example usage: obj.required_data_names(cls, train, inference) and returns: retval