code: def _maybe_extract(data_dir, extracted_data, archive):
      # If data_dir/extracted_data does not exist, extract archive in data_dir
      if not gfile.Exists(path.join(data_dir, extracted_data)):
          tar = tarfile.open(archive)
          tar.extractall(data_dir)
          tar.close()
  
file_path: DeepSpeech/bin/import_ted.py
imports: import sys
  import tarfile
  import unicodedata
  import wave
  from glob import glob
  from os import makedirs, path, remove, rmdir
  import pandas
  from sox import Transformer
  from tensorflow.python.platform import gfile
  from deepspeech_training.util.downloader import maybe_download
  from deepspeech_training.util.stm import parse_stm_file
label_desc: Use image node_id 2 for calling a global function with example usage: _maybe_extract(data_dir, extracted_data, archive) without return types