code: def test_get_random_layer_generator(load_mnist_model):
      model = PyTorchModel(load_mnist_model, channel_first=True)
  
      for (
          layer_name,
          random_layer_model,
      ) in model.get_random_layer_generator():
          layer = getattr(model.get_model(), layer_name).parameters()
          new_layer = getattr(
              random_layer_model, layer_name
          ).parameters()
  
          assert layer != new_layer, "Test failed."
  
file_path: Quantus/tests/functions/test_pytorch_model.py
imports: from collections import OrderedDict
  from typing import Union
  import numpy
  import pytest
  import torch
  from pytest_lazyfixture import lazy_fixture
  from scipy.special import softmax
  from quantus.helpers.model.pytorch_model import PyTorchModel
label_desc: Use image node_id 7 for calling a global function with example usage: test_get_random_layer_generator(load_mnist_model) without return types