code: def setup_training_data(
      self, train_data_config: Optional[DictConfig]
  ):
      self._train_dl = self._setup_dataloader_from_config(
          cfg=train_data_config
      )
  
imports: import os
  import pathlib
  from typing import Dict, List, Optional
  import torch
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from torch.utils.data import DataLoader
  from nemo.collections.common.losses import AggregatorLoss, CrossEntropyLoss
  from nemo.collections.nlp.data.intent_slot_classification import IntentSlotClassificationDataset, IntentSlotDataDesc, IntentSlotInferenceDataset
  from nemo.collections.nlp.metrics.classification_report import ClassificationReport
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.collections.nlp.modules.common import SequenceTokenClassifier
  from nemo.collections.nlp.parts.utils_funcs import tensor2list
  from nemo.core.classes import typecheck
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.utils import logging
label_desc: Use image node_id 14 for calling the IntentSlotClassificationModel obj's underlying member method code with example usage: obj.setup_training_data(train_data_config) without return types