code: def _download_and_preprocess_data(target_dir):
      # Making path absolute
      target_dir = os.path.abspath(target_dir)
      # Conditionally download data
      archive_path = maybe_download(
          ARCHIVE_NAME, target_dir, ARCHIVE_URL
      )
      # Conditionally extract data
      _maybe_extract(target_dir, ARCHIVE_DIR_NAME, archive_path)
      # Produce CSV files
      _maybe_convert_sets(target_dir, ARCHIVE_DIR_NAME)
  
file_path: DeepSpeech/bin/import_slr57.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 1 for calling a global function with example usage: _download_and_preprocess_data(target_dir) without return types