code: def parse_args():
      parser = argparse.ArgumentParser(
          description="Train a unigram tokenizer on the wikitext dataset."
      )
      parser.add_argument(
          "--dataset_name",
          type=str,
          default="wikitext",
          help="Name of the training. Explore datasets at: hf.co/datasets.",
      )
      parser.add_argument(
          "--dataset_config",
          type=str,
          default="wikitext-103-raw-v1",
          help="Configuration name of the dataset.",
      )
      parser.add_argument(
          "--batch_size",
          type=int,
          default=1000,
          help="Batch size during training.",
      )
      parser.add_argument(
          "--vocab_size",
          type=int,
          default=10048,
          help="Size of the desired vocabulary.",
      )
      parser.add_argument(
          "--limit",
          default=None,
          type=int,
          help="Limit the number of shards (used for debugging).",
      )
      parser.add_argument(
          "--export_to_hub",
          action="store_true",
      )
  
      args = parser.parse_args()
      return args
  
file_path: transformers/examples/tensorflow/language-modeling-tpu/train_unigram.py
imports: import argparse
  import logging
  import datasets
  from tokenizers import Tokenizer, decoders, normalizers, pre_tokenizers, processors
  from tokenizers.models import Unigram
  from tokenizers.trainers import UnigramTrainer
  from transformers import AlbertTokenizerFast
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args