code: def test_adapt_with_model_with_preprocessing_layer_only():
      input_node = keras.Input(shape=(10,))
      output_node = (
          keras.layers.experimental.preprocessing.Normalization()(
              input_node
          )
      )
      model = keras.Model(input_node, output_node)
      greedy.Greedy.adapt(
          model,
          tf.data.Dataset.from_tensor_slices(
              (np.random.rand(100, 10), np.random.rand(100, 10))
          ).batch(32),
      )
  
imports: from unittest import mock
  import numpy
  import tensorflow
  from tensorflow import keras
  from tensorflow.keras.layers.experimental import preprocessing
  import autokeras
  from autokeras import keras_layers
  from autokeras import test_utils
  from autokeras.engine import tuner
  from autokeras.tuners import greedy
label_desc: Use image node_id 11 for calling a global function with example usage: test_adapt_with_model_with_preprocessing_layer_only() without return types