code: def _test_integration(self, module, clf_name, plugins=[]):
      module = as_multitask(module, clf_name)
      module = module.to(self.device)
      optimizer = SGD(
          module.parameters(),
          lr=0.05,
          momentum=0.9,
          weight_decay=0.0002,
      )
  
      strategy = Naive(
          module,
          optimizer,
          train_mb_size=32,
          eval_mb_size=32,
          device=self.device,
          plugins=plugins,
      )
  
      for t, experience in enumerate(self.benchmark.train_stream):
          strategy.train(experience)
          strategy.eval(self.benchmark.test_stream[: t + 1])
  
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 8 for calling the ConversionMethodTests obj's underlying member method code with example usage: obj._test_integration(module, clf_name, plugins) without return types