code: def test_quantize_inc_ptq_compiled_additional_attributes(self):
      # Test if a Lightning Module compiled by nano works
      train_loader_iter = iter(self.train_loader)
      pl_model = Trainer.compile(self.model, self.loss, self.optimizer)
      # patch a attribute
      pl_model.channels = 3
  
      def hello():
          print("hello world!")
  
      # patch a function
      pl_model.hello = hello
      x = next(train_loader_iter)[0]
  
      qmodel = InferenceOptimizer.quantize(
          pl_model, calib_data=self.train_loader, thread_num=2
      )
      assert qmodel
      assert qmodel.channels == 3
      qmodel.hello()
      with pytest.raises(
          AttributeError,
          match="'PytorchQuantizedModel' object has no attribute 'width'",
      ):
          qmodel.width
  
      with InferenceOptimizer.get_context(qmodel):
          assert torch.get_num_threads() == 2
          out = qmodel(x)
      assert out.shape == torch.Size([256, 10])
  
      # save & load with original model
      with tempfile.TemporaryDirectory() as tmp_dir_name:
          InferenceOptimizer.save(qmodel, tmp_dir_name)
          load_model = InferenceOptimizer.load(
              tmp_dir_name, model=pl_model
          )
      assert load_model.channels == 3
      load_model.hello()
      with pytest.raises(
          AttributeError,
          match="'PytorchQuantizedModel' object has no attribute 'width'",
      ):
          load_model.width
  
imports: import os
  import operator
  import tempfile
  from unittest import TestCase
  import pytest
  import torch
  from pytorch_lightning import LightningModule
  from torch import nn
  from test.pytorch.utils._train_torch_lightning import create_data_loader, data_transform
  import torchmetrics
  from torchvision.models import resnet18
  from bigdl.nano.pytorch import Trainer
  from bigdl.nano.pytorch import InferenceOptimizer
  from bigdl.nano.pytorch.vision.models import vision
  from bigdl.nano.utils.common import invalidOperationError
  from bigdl.nano.utils.common import compare_version
  from bigdl.nano.utils.pytorch import TORCH_VERSION_LESS_2_0
  from bigdl.nano.utils.common import _avx2_checker
label_desc: Use image node_id 5 for calling the TestINC obj's underlying member method code with example usage: obj.test_quantize_inc_ptq_compiled_additional_attributes() without return types