code: def load_cifar10():
      """Loads CIFAR10, with training and test combined."""
      (x_train, y_train), (
          x_test,
          y_test,
      ) = tf.keras.datasets.cifar10.load_data()
      x = np.concatenate([x_train, x_test]).astype(np.float32) / 255
      y = np.concatenate([y_train, y_test]).astype(np.int32).squeeze()
      return x, y
  
file_path: privacy/tensorflow_privacy/privacy/privacy_tests/membership_inference_attack/advanced_mia_example.py
imports: import functools
  import gc
  import os
  from typing import Optional
  from absl import app
  from absl import flags
  import matplotlib.pyplot
  import numpy
  import tensorflow
  from tensorflow_privacy.privacy.privacy_tests import utils
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack import advanced_mia
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack import membership_inference_attack
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack import plotting
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import AttackInputData
label_desc: Use image node_id 2 for calling a global function with example usage: load_cifar10() and returns: x,  y