code: def small_cnn():
      """Setup a small CNN for image classification."""
      model = tf.keras.models.Sequential()
      model.add(tf.keras.layers.Input(shape=(32, 32, 3)))
  
      for _ in range(3):
          model.add(
              tf.keras.layers.Conv2D(32, (3, 3), activation="relu")
          )
          model.add(tf.keras.layers.MaxPooling2D())
  
      model.add(tf.keras.layers.Flatten())
      model.add(tf.keras.layers.Dense(64, activation="relu"))
      model.add(tf.keras.layers.Dense(10))
      return model
  
file_path: privacy/tensorflow_privacy/privacy/privacy_tests/membership_inference_attack/keras_evaluation_example.py
imports: from absl import app
  from absl import flags
  import numpy
  import tensorflow
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import AttackType
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import get_flattened_attack_metrics
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import SlicingSpec
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.keras_evaluation import MembershipInferenceCallback
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.keras_evaluation import run_attack_on_keras_model
label_desc: Use image node_id 1 for calling a global function with example usage: small_cnn() and returns: model