code: def test_initialisation(self):
      module = SimpleMLP()
      module = module.to(self.device)
      old_classifier_weight = torch.clone(module.classifier.weight)
      old_classifier_bias = torch.clone(module.classifier.bias)
      module = as_multitask(module, "classifier")
      module = module.to(self.device)
      new_classifier_weight = torch.clone(
          module.classifier.classifiers["0"].classifier.weight
      )
      new_classifier_bias = torch.clone(
          module.classifier.classifiers["0"].classifier.bias
      )
      self.assertTrue(
          torch.equal(old_classifier_weight, new_classifier_weight)
      )
      self.assertTrue(
          torch.equal(old_classifier_bias, new_classifier_bias)
      )
  
file_path: avalanche/tests/models/test_helper_method.py
imports: import copy
  import unittest
  import torch
  from torch.optim import SGD
  from avalanche.models import SimpleCNN, SimpleMLP, as_multitask
  from avalanche.models.dynamic_modules import MultiTaskModule, MultiHeadClassifier
  from avalanche.training.plugins import LwFPlugin, EWCPlugin
  from avalanche.training.supervised import Naive
  from tests.unit_tests_utils import common_setups, get_fast_benchmark, get_device
label_desc: Use image node_id 5 for calling the ConversionMethodTests obj's underlying member method code with example usage: obj.test_initialisation() without return types