code: def _maybe_extract(target_dir, extracted_data, archive_path):
      # If target_dir/extracted_data does not exist, extract archive in target_dir
      extracted_path = os.path.join(target_dir, extracted_data)
      if not os.path.exists(extracted_path):
          print(
              'No directory "%s" - extracting archive...'
              % extracted_path
          )
          if not os.path.isdir(extracted_path):
              os.mkdir(extracted_path)
          tar = tarfile.open(archive_path)
          tar.extractall(extracted_path)
          tar.close()
      else:
          print(
              'Found directory "%s" - not extracting it from archive.'
              % archive_path
          )
  
file_path: DeepSpeech/bin/import_m-ailabs.py
imports: import csv
  import os
  import subprocess
  import tarfile
  import unicodedata
  from glob import glob
  from multiprocessing import Pool
  import progressbar
  from deepspeech_training.util.downloader import SIMPLE_BAR, maybe_download
  from deepspeech_training.util.importers import get_counter, get_imported_samples, get_importers_parser, get_validate_label, print_import_report
  from ds_ctcdecoder import Alphabet
label_desc: Use image node_id 2 for calling a global function with example usage: _maybe_extract(target_dir, extracted_data, archive_path) without return types