code: def setup_training_data(
      self, train_data_config: Optional[DictConfig]
  ):
      if not train_data_config or not train_data_config.file:
          logging.info(
              f"Dataloader config or file_path for the train is missing, so no data loader for test is created!"
          )
          self._test_dl = None
          return
  
      self._train_dl = self._setup_dataloader_from_config(
          cfg=train_data_config, mode=TRAINING_MODE
      )
  
file_path: NeMo/nemo/collections/nlp/models/question_answering/qa_base_model.py
imports: from typing import Optional
  import torch
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from nemo.collections.nlp.data.question_answering.data_processor.qa_processing import EVALUATION_MODE, INFERENCE_MODE, TRAINING_MODE
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.utils import logging
label_desc: Use image node_id 2 for calling the BaseQAModel obj's underlying member method code with example usage: obj.setup_training_data(train_data_config) without return types