code: def main():
      # Initialize the classifier.
      train_file_path = tf.keras.utils.get_file(
          "train.csv", TRAIN_DATA_URL
      )
      test_file_path = tf.keras.utils.get_file(
          "eval.csv", TEST_DATA_URL
      )
      clf = ak.StructuredDataClassifier(
          max_trials=10, directory="tmp_dir", overwrite=True
      )
  
      start_time = timeit.default_timer()
      # x is the path to the csv file. y is the column name of the column to
      # predict.
      clf.fit(train_file_path, "survived")
      stop_time = timeit.default_timer()
  
      # Evaluate the accuracy of the found model.
      accuracy = clf.evaluate(test_file_path, "survived")[1]
      print(
          "Accuracy: {accuracy}%".format(
              accuracy=round(accuracy * 100, 2)
          )
      )
      print(
          "Total time: {time} seconds.".format(
              time=round(stop_time - start_time, 2)
          )
      )
  
imports: import timeit
  import tensorflow
  import autokeras
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types