code: def main():
      parser = argparse.ArgumentParser()
  
      parser.add_argument(
          "-csv",
          "--csv-files",
          help="Str. Filenames as a comma separated list",
          required=True,
      )
      parser.add_argument(
          "--sample-rate",
          type=int,
          default=16000,
          required=False,
          help="Audio sample rate",
      )
      parser.add_argument(
          "--channels",
          type=int,
          default=1,
          required=False,
          help="Audio channels",
      )
      parser.add_argument(
          "--bits-per-sample",
          type=int,
          default=16,
          required=False,
          help="Audio bits per sample",
      )
      args = parser.parse_args()
      in_files = [Path(i).absolute() for i in args.csv_files.split(",")]
  
      csv_dataframe = read_csvs(in_files)
      total_bytes = csv_dataframe["wav_filesize"].sum()
      total_files = len(csv_dataframe)
      total_seconds = (
          (csv_dataframe["wav_filesize"] - 44)
          / args.sample_rate
          / args.channels
          / (args.bits_per_sample // 8)
      ).sum()
  
      print("Total bytes:", total_bytes)
      print("Total files:", total_files)
      print("Total time:", secs_to_hours(total_seconds))
  
imports: import argparse
  import functools
  import pandas
  from deepspeech_training.util.helpers import secs_to_hours
  from pathlib import Path
label_desc: Use image node_id 2 for calling a global function with example usage: main() without return types