code: def train(
      self,
      train_data: Optional[Union[str, DataFrame]] = None,
      validate_data: Optional[Union[str, DataFrame]] = None,
      output_dir: str = None,
      saved_model_path: str = None,
  ) -> None:
      train_set = self._prepare_data(train_data, "train_data")
      validate_set = self._prepare_data(validate_data, "val_data")
  
      if self.is_guest():
          self._check_label(train_set)
          if validate_set is not None:
              self._check_label(validate_set)
          trainer, model = self.guest_setup(
              train_set, validate_set, output_dir, saved_model_path
          )
      elif self.is_host():
          trainer, model = self.host_setup(
              train_set, validate_set, output_dir, saved_model_path
          )
      else:
          raise RuntimeError("invalid role in hetero nn")
  
      self.trainer, self.model = trainer, model
      self.trainer.train()
      if output_dir is not None:
          self.trainer.save_model(output_dir)
  
imports: import logging
  from fate.components.components.nn.loader import Loader
  from typing import Optional, Union, Dict, Literal
  from fate.arch.dataframe import DataFrame
  from fate.components.components.nn.nn_runner import NNRunner, loader_load_from_conf, load_model_dict_from_path, dir_warning, run_dataset_func
  from transformers.trainer_utils import get_last_checkpoint
  from fate.ml.nn.hetero.hetero_nn import HeteroNNTrainerGuest, HeteroNNTrainerHost, TrainingArguments
  from fate.ml.nn.model_zoo.hetero_nn_model import HeteroNNModelGuest, HeteroNNModelHost
  from fate.components.components.utils import consts
  from fate.ml.nn.dataset.table import TableDataset, Dataset
  from fate.ml.nn.model_zoo.hetero_nn_model import FedPassArgument, StdAggLayerArgument, parse_agglayer_conf, TopModelStrategyArguments
label_desc: Use image node_id 7 for calling the DefaultRunner obj's underlying member method code with example usage: obj.train(train_data, validate_data, output_dir, saved_model_path) without return types