code: def main():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--train_file_path",
          required=True,
          help="this is the path to the train.txt file that the preprocess.py script creates",
      )
      parser.add_argument(
          "--save_to", help="path to save charts of data to"
      )
      parser.add_argument(
          "--cmu_dict_path",
          help="give cmudict-0.7b to see phoneme distribution",
      )
      args = parser.parse_args()
      meta_data = process_meta_data(args.train_file_path)
      plt.rcParams["figure.figsize"] = (10, 5)
      plot(meta_data, save_path=args.save_to)
      if args.cmu_dict_path:
          plt.rcParams["figure.figsize"] = (30, 10)
          plot_phonemes(
              args.train_file_path, args.cmu_dict_path, args.save_to
          )
  
      plt.show()
  
file_path: TTS/notebooks/dataset_analysis/analyze.py
imports: import matplotlib.pyplot
  from statistics import stdev, mode, mean, median
  from statistics import StatisticsError
  import argparse
  import os
  import csv
  import seaborn
  import random
  from text.cmudict import CMUDict
label_desc: Use image node_id 8 for calling a global function with example usage: main() without return types