code: def one_sample(sample):
      """Take a audio file, and optionally convert it to 16kHz WAV"""
      ogg_filename = sample[0]
      # Storing wav files next to the ogg ones - just with a different suffix
      wav_filename = os.path.splitext(ogg_filename)[0] + ".wav"
      _maybe_convert_wav(ogg_filename, wav_filename)
      file_size = -1
      frames = 0
      if os.path.exists(wav_filename):
          file_size = os.path.getsize(wav_filename)
          frames = int(
              subprocess.check_output(
                  ["soxi", "-s", wav_filename], stderr=subprocess.STDOUT
              )
          )
      label = label_filter(sample[1])
      rows = []
      counter = get_counter()
  
      if file_size == -1:
          # Excluding samples that failed upon conversion
          counter["failed"] += 1
      elif label is None:
          # Excluding samples that failed on label validation
          counter["invalid_label"] += 1
      elif int(frames / SAMPLE_RATE * 1000 / 10 / 2) < len(str(label)):
          # Excluding samples that are too short to fit the transcript
          counter["too_short"] += 1
      elif frames / SAMPLE_RATE > MAX_SECS:
          # Excluding very long samples to keep a reasonable batch-size
          counter["too_long"] += 1
      else:
          # This one is good - keep it for the target CSV
          rows.append((wav_filename, file_size, label))
          counter["imported_time"] += frames
      counter["all"] += 1
      counter["total_time"] += frames
  
      return (counter, rows)
  
file_path: DeepSpeech/bin/import_lingua_libre.py
imports: import argparse
  import csv
  import os
  import re
  import subprocess
  import unicodedata
  import zipfile
  from glob import glob
  from multiprocessing import Pool
  import progressbar
  import sox
  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 3 for calling a global function with example usage: one_sample(sample) and returns: counter,  rows