code: def _setup_dataloader_from_config(
      self, cfg: DictConfig, dataset_split: str
  ):
      data_processor = DialogueAssistantDataProcessor(
          self.data_dir, self.tokenizer, cfg=self.cfg.dataset
      )
  
      dataset = DialogueBERTDataset(
          dataset_split,
          data_processor,
          self.tokenizer,
          self.cfg.dataset,  # this is the model.dataset cfg, which is diff from train_ds cfg etc
      )
  
      return DataLoader(
          dataset=dataset,
          batch_size=cfg.batch_size,
          shuffle=cfg.shuffle,
          num_workers=cfg.num_workers,
          pin_memory=cfg.pin_memory,
          drop_last=cfg.drop_last,
          collate_fn=dataset.collate_fn,
      )
  
imports: import os
  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.dialogue.data_processor.assistant_data_processor import DialogueAssistantDataProcessor
  from nemo.collections.nlp.data.dialogue.dataset.dialogue_bert_dataset import DialogueBERTDataset, DialogueIntentSlotInferenceDataset
  from nemo.collections.nlp.data.intent_slot_classification import IntentSlotDataDesc
  from nemo.collections.nlp.metrics.classification_report import ClassificationReport
  from nemo.collections.nlp.metrics.dialogue_metrics import DialogueClassificationMetrics
  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 20 for calling the IntentSlotClassificationModel obj's underlying member method code with example usage: obj._setup_dataloader_from_config(cfg, dataset_split) and returns: DataLoader