code: def add_arguments(parser: argparse.ArgumentParser):
      parser.add_argument(
          "--data_file",
          default=None,
          type=str,
          required=True,
          help="The data file containing data for inference",
      )
      parser.add_argument(
          "--model_dir",
          type=str,
          required=True,
          help="Path to trained model directory",
      )
      parser.add_argument(
          "--output_dir",
          type=str,
          required=True,
          help="Output directory where the model will be saved",
      )
      parser.add_argument(
          "--overwrite_output_dir",
          action="store_true",
          help="Overwrite the content of the output directory",
      )
      parser.add_argument(
          "--no_cuda",
          action="store_true",
          help="Avoid using CUDA when available",
      )
      parser.add_argument(
          "-b", type=int, default=100, help="Batch size"
      )
  
imports: import argparse
  import io
  import os
  import torch
  from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
  from nlp_architect.data.sequential_tagging import TokenClsInputExample, TokenClsProcessor
  from nlp_architect.data.utils import write_column_tagged_file
  from nlp_architect.models.tagging import NeuralTagger
  from nlp_architect.nn.torch.modules.embedders import IDCNN, CNNLSTM
  from nlp_architect.nn.torch import setup_backend, set_seed
  from nlp_architect.nn.torch.distillation import TeacherStudentDistill
  from nlp_architect.procedures.procedure import Procedure
  from nlp_architect.procedures.registry import register_train_cmd, register_inference_cmd
  from nlp_architect.utils.embedding import get_embedding_matrix, load_embedding_file
  from nlp_architect.utils.io import prepare_output_path
  from nlp_architect.utils.text import SpacyInstance
  from nlp_architect.nn.torch.data.dataset import ParallelDataset, ConcatTensorDataset, CombinedTensorDataset
  from nlp_architect.models.transformers import TransformerTokenClassifier
label_desc: Use image node_id 1 for calling the RunTagger obj's underlying member method code with example usage: obj.add_arguments(parser) without return types