code: def load_cifar10_images():
      """Load a batch of MNIST digits: inputs and outputs to use for testing."""
      (x_train, y_train), (_, _) = cifar10.load_data()
      x_batch = (
          x_train[:BATCH_SIZE]
          .reshape((BATCH_SIZE, 3, CIFAR_IMAGE_SIZE, CIFAR_IMAGE_SIZE))
          .astype(float)
      )[:MINI_BATCH_SIZE]
      y_batch = (
          y_train[:BATCH_SIZE].reshape(-1).astype(int)[:MINI_BATCH_SIZE]
      )
      return {"x_batch": x_batch, "y_batch": y_batch}
  
imports: import pytest
  import pickle
  import torch
  import numpy
  from keras.datasets import cifar10
  import pandas
  from sklearn.model_selection import train_test_split
  import os
  from quantus.helpers.model.models import LeNet, LeNetTF, CifarCNNModel, ConvNet1D, ConvNet1DTF, TitanicSimpleTFModel, TitanicSimpleTorchModel
label_desc: Use image node_id 8 for calling a global function with example usage: load_cifar10_images() and returns: dict