code: def main(
      input_data_dir,
      working_dir,
      read_raw_data_for_training=True,
      num_train_instances=common.NUM_TRAIN_INSTANCES,
      num_test_instances=common.NUM_TEST_INSTANCES,
  ):
      if not working_dir:
          working_dir = tempfile.mkdtemp(dir=input_data_dir)
  
      train_data_file = os.path.join(input_data_dir, "adult.data")
      test_data_file = os.path.join(input_data_dir, "adult.test")
  
      common.transform_data(
          train_data_file, test_data_file, working_dir
      )
  
      if read_raw_data_for_training:
          raw_train_and_eval_patterns = (
              train_data_file,
              test_data_file,
          )
          transformed_train_and_eval_patterns = None
      else:
          train_pattern = os.path.join(
              working_dir, common.TRANSFORMED_TRAIN_DATA_FILEBASE + "*"
          )
          eval_pattern = os.path.join(
              working_dir, common.TRANSFORMED_TEST_DATA_FILEBASE + "*"
          )
          raw_train_and_eval_patterns = None
          transformed_train_and_eval_patterns = (
              train_pattern,
              eval_pattern,
          )
      output_dir = os.path.join(working_dir, common.EXPORTED_MODEL_DIR)
      results = train_and_evaluate(
          raw_train_and_eval_patterns,
          transformed_train_and_eval_patterns,
          output_dir,
          working_dir,
          num_train_instances=num_train_instances,
          num_test_instances=num_test_instances,
      )
  
      pprint.pprint(results)
  
file_path: transform/examples/census_example_v2.py
imports: import math
  import os
  import pprint
  import tempfile
  from absl import logging
  import tensorflow
  import tensorflow_transform
  import census_example_common
  from tensorflow_transform.keras_lib import tf_keras
label_desc: Use image node_id 5 for calling a global function with example usage: main(input_data_dir, working_dir, read_raw_data_for_training, num_train_instances, num_test_instances) without return types