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(
              f"No directory {extracted_path} - extracting archive..."
          )
          with ZipFile(archive_path, "r") as zipobj:
              # Extract all the contents of zip file in current directory
              zipobj.extractall(target_dir)
      else:
          print(
              f"Found directory {extracted_path} - not extracting it from archive."
          )
  
file_path: DeepSpeech/bin/import_vctk.py
imports: import os
  import random
  import re
  from multiprocessing import Pool
  from zipfile import ZipFile
  import librosa
  import progressbar
  from deepspeech_training.util.downloader import SIMPLE_BAR, maybe_download
  from deepspeech_training.util.importers import get_counter, get_imported_samples, print_import_report
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