code: def main():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "input_data_dir",
          help="path to directory containing input data",
      )
      parser.add_argument(
          "--working_dir",
          help="path to directory to hold transformed data",
      )
      args = parser.parse_args()
  
      if args.working_dir:
          working_dir = args.working_dir
      else:
          working_dir = tempfile.mkdtemp(dir=args.input_data_dir)
  
      train_neg_filepattern = os.path.join(
          args.input_data_dir, "train/neg/*"
      )
      train_pos_filepattern = os.path.join(
          args.input_data_dir, "train/pos/*"
      )
      test_neg_filepattern = os.path.join(
          args.input_data_dir, "test/neg/*"
      )
      test_pos_filepattern = os.path.join(
          args.input_data_dir, "test/pos/*"
      )
  
      read_and_shuffle_data(
          train_neg_filepattern,
          train_pos_filepattern,
          test_neg_filepattern,
          test_pos_filepattern,
          working_dir,
      )
      transform_data(working_dir)
      results = train_and_evaluate(working_dir)
  
      pprint.pprint(results)
  
file_path: transform/examples/sentiment_example.py
imports: import argparse
  import os
  import pprint
  import tempfile
  import apache_beam
  import tensorflow
  from tensorflow import estimator
  import tensorflow_transform
  import tensorflow_transform.beam
  from tfx_bsl.public import tfxio
label_desc: Use image node_id 9 for calling a global function with example usage: main() without return types