code: def build_fake_data():
      """Build fake CIFAR10-style data for unit testing."""
      num_examples = 10
      x_train = np.random.rand(num_examples, *IMAGE_SHAPE).astype(
          np.float32
      )
      y_train = np.random.permutation(np.arange(num_examples)).astype(
          np.int32
      )
      x_test = np.random.rand(num_examples, *IMAGE_SHAPE).astype(
          np.float32
      )
      y_test = np.random.permutation(np.arange(num_examples)).astype(
          np.int32
      )
      return (x_train, y_train), (x_test, y_test)
  
file_path: probability/tensorflow_probability/examples/cifar10_bnn.py
imports: import os
  import warnings
  from absl import flags
  import matplotlib
  import numpy
  import tensorflow.compat.v1
  import tensorflow_probability
  from tensorflow_probability.examples.models.bayesian_resnet import bayesian_resnet
  from tensorflow_probability.examples.models.bayesian_vgg import bayesian_vgg
  from tensorflow_probability.python.internal import tf_keras
label_desc: Use image node_id 2 for calling a global function with example usage: build_fake_data() and returns: x_train,  y_train,  x_test,  y_test