code: def main() -> None:
      args = get_args()
      if args.special_token_names is None:
          special_tokens = None
      else:
          special_tokens = dict(
              zip(args.special_token_names, args.special_token_values)
          )
  
      if args.punct_labels is not None:
          punct_label_ids = build_label_ids_from_list_of_labels(
              args.pad_label, args.punct_labels
          )
      else:
          punct_label_ids = None
  
      if args.capit_labels is not None:
          capit_label_ids = build_label_ids_from_list_of_labels(
              args.pad_label, args.capit_labels
          )
      else:
          capit_label_ids = None
  
      create_tarred_dataset(
          args.text,
          args.labels,
          args.output_dir,
          args.max_seq_length,
          args.tokens_in_batch,
          args.lines_per_dataset_fragment,
          args.num_batches_per_tarfile,
          args.tokenizer_name,
          tokenizer_model=args.tokenizer_model,
          vocab_file=args.vocab_file,
          merges_file=args.merges_file,
          special_tokens=special_tokens,
          use_fast_tokenizer=args.use_fast_tokenizer,
          pad_label=args.pad_label,
          punct_label_ids=punct_label_ids,
          capit_label_ids=capit_label_ids,
          punct_label_vocab_file=args.punct_label_vocab_file,
          capit_label_vocab_file=args.capit_label_vocab_file,
          tar_file_prefix=args.tar_file_prefix,
          n_jobs=args.n_jobs,
          audio_file=args.audio_file,
          sample_rate=args.sample_rate,
          use_audio=args.use_audio,
      )
  
imports: import argparse
  import multiprocessing
  from pathlib import Path
  from nemo.collections.nlp.data.token_classification.punctuation_capitalization_tarred_dataset import DEFAULT_CAPIT_LABEL_VOCAB_FILE_NAME, DEFAULT_PUNCT_LABEL_VOCAB_FILE_NAME, METADATA_CAPIT_LABEL_VOCAB_KEY, METADATA_PUNCT_LABEL_VOCAB_KEY, build_label_ids_from_list_of_labels, check_labels_for_being_unique_before_building_label_ids, check_tar_file_prefix, create_tarred_dataset
label_desc: Use image node_id 2 for calling a global function with example usage: main() without return types