code: def add_glue_args(parser: argparse.ArgumentParser):
      parser.add_argument(
          "--task_name",
          default=None,
          type=str,
          required=True,
          help="The name of the task to train selected in the list: "
          + ", ".join(processors.keys()),
      )
      parser.add_argument(
          "--data_dir",
          default=None,
          type=str,
          required=True,
          help="The input data dir. Should contain dataset files to be parsed "
          + "by the dataloaders.",
      )
  
imports: import argparse
  import io
  import logging
  import os
  from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
  from nlp_architect.data.glue_tasks import get_glue_task, get_metric_fn, processors
  from nlp_architect.models.transformers import TransformerSequenceClassifier
  from nlp_architect.nn.torch import set_seed, setup_backend
  from nlp_architect.procedures.procedure import Procedure
  from nlp_architect.procedures.registry import register_inference_cmd, register_train_cmd
  from nlp_architect.procedures.transformers.base import create_base_args, inference_args, train_args
  from nlp_architect.utils.io import prepare_output_path
label_desc: Use image node_id 1 for calling a global function with example usage: add_glue_args(parser) without return types