code: def load_mnist_model():
      """Load a pre-trained LeNet classification model (architecture at quantus/helpers/models)."""
      model = LeNet()
      model.load_state_dict(
          torch.load(
              "tests/assets/mnist",
              map_location="cpu",
              pickle_module=pickle,
          )
      )
      return model
  
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 1 for calling a global function with example usage: load_mnist_model() and returns: model