code: def test_clf_head_hpps_with_uint8_contain_cast_to_int32():
      dataset = test_utils.generate_one_hot_labels(100, 10, "dataset")
      dataset = dataset.map(lambda x: tf.cast(x, tf.uint8))
      head = head_module.ClassificationHead(shape=(8,))
      analyser = head.get_analyser()
      for data in dataset:
          analyser.update(data)
      analyser.finalize()
      head.config_from_analyser(analyser)
  
      assert any(
          [
              isinstance(
                  hpp, hyper_preprocessors.DefaultHyperPreprocessor
              )
              and isinstance(
                  hpp.preprocessor, preprocessors.CastToInt32
              )
              for hpp in head.get_hyper_preprocessors()
          ]
      )
  
file_path: autokeras/autokeras/blocks/heads_test.py
imports: import keras_tuner
  import numpy
  import tensorflow
  from tensorflow import keras
  from tensorflow import nest
  import autokeras
  from autokeras import hyper_preprocessors
  from autokeras import nodes
  from autokeras import preprocessors
  from autokeras import test_utils
  from autokeras.blocks import heads
label_desc: Use image node_id 7 for calling a global function with example usage: test_clf_head_hpps_with_uint8_contain_cast_to_int32() without return types