code: def add_arguments(parser: argparse.ArgumentParser):
      add_glue_args(parser)
      create_base_args(
          parser,
          model_types=TransformerSequenceClassifier.MODEL_CLASS.keys(),
      )
      train_args(
          parser,
          models_family=TransformerSequenceClassifier.MODEL_CLASS.keys(),
      )
  
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 the TransformerGlueTrain obj's underlying member method code with example usage: obj.add_arguments(parser) without return types