code: def add_model_specific_args(parser, root_dir):
      BaseTransformer.add_model_specific_args(parser, root_dir)
      parser.add_argument(
          "--max_seq_length",
          default=128,
          type=int,
          help=(
              "The maximum total input sequence length after tokenization. Sequences longer "
              "than this will be truncated, sequences shorter will be padded."
          ),
      )
  
      parser.add_argument(
          "--task",
          default="",
          type=str,
          required=True,
          help="The GLUE task to run",
      )
      parser.add_argument(
          "--gpus",
          default=0,
          type=int,
          help="The number of GPUs allocated for this, it is by default 0 meaning none",
      )
  
      parser.add_argument(
          "--overwrite_cache",
          action="store_true",
          help="Overwrite the cached training and evaluation sets",
      )
  
      return parser
  
imports: import argparse
  import glob
  import logging
  import os
  import time
  from argparse import Namespace
  import numpy
  import torch
  from torch.utils.data import DataLoader, TensorDataset
  from lightning_base import BaseTransformer, add_generic_args, generic_train
  from transformers import glue_compute_metrics
  from transformers import glue_convert_examples_to_features
  from transformers import glue_output_modes
  from transformers import glue_processors
  from transformers import glue_tasks_num_labels
label_desc: Use image node_id 10 for calling the GLUETransformer obj's underlying member method code with example usage: obj.add_model_specific_args(parser, root_dir) and returns: parser