code: def load_cifar10():
      """Loads CIFAR10 data."""
      (x_train, y_train), (
          x_test,
          y_test,
      ) = tf.keras.datasets.cifar10.load_data()
  
      x_train = np.array(x_train, dtype=np.float32) / 255
      x_test = np.array(x_test, dtype=np.float32) / 255
  
      y_train = np.array(y_train, dtype=np.int32).squeeze()
      y_test = np.array(y_test, dtype=np.int32).squeeze()
  
      return x_train, y_train, x_test, y_test
  
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 2 for calling a global function with example usage: load_cifar10() and returns: x_train,  y_train,  x_test,  y_test