code: def _download_and_preprocess_data(
      target_dir, english_compatible=False
  ):
      # Making path absolute
      target_dir = os.path.abspath(target_dir)
      # Conditionally download data
      archive_path = maybe_download(
          "ts_" + ARCHIVE_NAME + ".zip", target_dir, ARCHIVE_URL
      )
      # Conditionally extract archive data
      _maybe_extract(target_dir, ARCHIVE_DIR_NAME, archive_path)
      # Conditionally convert TrainingSpeech data to DeepSpeech CSVs and wav
      _maybe_convert_sets(
          target_dir,
          ARCHIVE_DIR_NAME,
          english_compatible=english_compatible,
      )
  
file_path: DeepSpeech/bin/import_ts.py
imports: import csv
  import os
  import re
  import subprocess
  import zipfile
  from multiprocessing import Pool
  import progressbar
  import sox
  import unidecode
  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
label_desc: Use image node_id 1 for calling a global function with example usage: _download_and_preprocess_data(target_dir, english_compatible) without return types