code: def _preprocess_data(
      tsv_dir, audio_dir, space_after_every_character=False
  ):
      exclude = []
      for dataset in ["test", "dev", "train", "validated", "other"]:
          set_samples = _maybe_convert_set(
              dataset, tsv_dir, audio_dir, space_after_every_character
          )
          if dataset in ["test", "dev"]:
              exclude += set_samples
          if dataset == "validated":
              _maybe_convert_set(
                  "train-all",
                  tsv_dir,
                  audio_dir,
                  space_after_every_character,
                  rows=set_samples,
                  exclude=exclude,
              )
  
file_path: DeepSpeech/bin/import_cv2.py
imports: import csv
  import os
  import subprocess
  import unicodedata
  from multiprocessing import Pool
  import progressbar
  import sox
  from deepspeech_training.util.downloader import SIMPLE_BAR
  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 4 for calling a global function with example usage: _preprocess_data(tsv_dir, audio_dir, space_after_every_character) without return types