code: def _setup_dataloader_from_config(
      self, cfg: Dict
  ) -> "torch.utils.data.DataLoader":
      input_file = cfg.file_path
      if not os.path.exists(input_file):
          raise FileNotFoundError(
              f'{input_file} not found! The data should be be stored in TAB-separated files \n\
                  "validation_ds.file_path" and "train_ds.file_path" for train and evaluation respectively. \n\
                  Each line of the files contains text sequences, where words are separated with spaces. \n\
                  The label of the example is separated with TAB at the end of each line. \n\
                  Each line of the files should follow the format: \n\
                  [WORD][SPACE][WORD][SPACE][WORD][...][TAB][LABEL]'
          )
  
      dataset = TextClassificationDataset(
          tokenizer=self.tokenizer,
          input_file=input_file,
          max_seq_length=self.dataset_cfg.max_seq_length,
          num_samples=cfg.get("num_samples", -1),
          shuffle=cfg.shuffle,
          use_cache=self.dataset_cfg.use_cache,
      )
  
      return torch.utils.data.DataLoader(
          dataset=dataset,
          batch_size=cfg.batch_size,
          shuffle=cfg.shuffle,
          num_workers=cfg.get("num_workers", 0),
          pin_memory=cfg.get("pin_memory", False),
          drop_last=cfg.get("drop_last", False),
          collate_fn=dataset.collate_fn,
      )
  
imports: import os
  from typing import Dict, List, Optional
  import torch
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from nemo.collections.common.losses import CrossEntropyLoss
  from nemo.collections.nlp.data.text_classification import TextClassificationDataset, calc_class_weights
  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 SequenceClassifier
  from nemo.collections.nlp.parts.utils_funcs import tensor2list
  from nemo.core.classes.common import typecheck
  from nemo.core.classes.exportable import Exportable
  from nemo.utils import logging
label_desc: Use image node_id 12 for calling the TextClassificationModel obj's underlying member method code with example usage: obj._setup_dataloader_from_config(cfg) and returns: torch