code: def _setup_dataloader_from_config(self, cfg: DictConfig):
      file_name = cfg.ds_item
      if not os.path.exists(file_name):
          raise FileNotFoundError(
              "GLUE datasets not found. For more details on how to get the data, see: "
              "https://gist.github.com/W4ngatang/60c2bdb54d156a41194446737ce03e2e"
          )
  
      dataset = GLUEDataset(
          file_name=file_name,
          task_name=self.task_name,
          tokenizer=self.tokenizer,
          max_seq_length=self._cfg.dataset.max_seq_length,
          use_cache=self._cfg.dataset.use_cache,
      )
  
      return torch.utils.data.DataLoader(
          dataset=dataset,
          collate_fn=dataset.collate_fn,
          batch_size=cfg.batch_size,
          shuffle=cfg.shuffle,
          num_workers=self._cfg.dataset.num_workers,
          pin_memory=self._cfg.dataset.pin_memory,
          drop_last=self._cfg.dataset.drop_last,
      )
  
imports: import os
  from typing import Dict, Optional, Union
  import numpy
  import torch
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from nemo.collections.common.losses import CrossEntropyLoss, MSELoss
  from nemo.collections.nlp.data.glue_benchmark.glue_benchmark_dataset import GLUE_TASKS_NUM_LABELS, GLUEDataset
  from nemo.collections.nlp.models.glue_benchmark.metrics_for_glue import compute_metrics
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.collections.nlp.modules.common import SequenceClassifier, SequenceRegression
  from nemo.collections.nlp.parts.utils_funcs import list2str, tensor2list
  from nemo.core.classes import typecheck
  from nemo.core.neural_types import NeuralType
  from nemo.utils import logging
label_desc: Use image node_id 13 for calling the GLUEModel obj's underlying member method code with example usage: obj._setup_dataloader_from_config(cfg) and returns: torch