code: def load_mnist_images():
      """Load a batch of MNIST digits: inputs and outputs to use for testing."""
      x_batch = (
          np.loadtxt("tests/assets/mnist_x")
          .astype(float)
          .reshape((BATCH_SIZE, 1, MNIST_IMAGE_SIZE, MNIST_IMAGE_SIZE))
      )[:MINI_BATCH_SIZE]
      y_batch = np.loadtxt("tests/assets/mnist_y").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 7 for calling a global function with example usage: load_mnist_images() and returns: dict