code: def test_getattr_is_correct(self):
      (
          init_dict,
          inputs_dict,
      ) = self.prepare_init_args_and_inputs_for_common()
      model = self.model_class(**init_dict)
  
      # save some things to test
      model.dummy_attribute = 5
      model.register_to_config(test_attribute=5)
  
      logger = logging.get_logger("diffusers.models.modeling_utils")
      # 30 for warning
      logger.setLevel(30)
      with CaptureLogger(logger) as cap_logger:
          assert hasattr(model, "dummy_attribute")
          assert getattr(model, "dummy_attribute") == 5
          assert model.dummy_attribute == 5
  
      # no warning should be thrown
      assert cap_logger.out == ""
  
      logger = logging.get_logger("diffusers.models.modeling_utils")
      # 30 for warning
      logger.setLevel(30)
      with CaptureLogger(logger) as cap_logger:
          assert hasattr(model, "save_pretrained")
          fn = model.save_pretrained
          fn_1 = getattr(model, "save_pretrained")
  
          assert fn == fn_1
      # no warning should be thrown
      assert cap_logger.out == ""
  
      # warning should be thrown
      with self.assertWarns(FutureWarning):
          assert model.test_attribute == 5
  
      with self.assertWarns(FutureWarning):
          assert getattr(model, "test_attribute") == 5
  
      with self.assertRaises(AttributeError) as error:
          model.does_not_exist
  
      assert (
          str(error.exception)
          == f"'{type(model).__name__}' object has no attribute 'does_not_exist'"
      )
  
imports: import inspect
  import tempfile
  import traceback
  import unittest
  import unittest.mock
  import uuid
  from typing import Dict, List, Tuple
  import numpy
  import requests_mock
  import torch
  from huggingface_hub import delete_repo
  from requests.exceptions import HTTPError
  from diffusers.models import UNet2DConditionModel
  from diffusers.models.attention_processor import AttnProcessor, AttnProcessor2_0, XFormersAttnProcessor
  from diffusers.training_utils import EMAModel
  from diffusers.utils import is_xformers_available, logging
  from diffusers.utils.testing_utils import CaptureLogger, require_python39_or_higher, require_torch_2, require_torch_gpu, run_test_in_subprocess, torch_device
  from ..others.test_utils import TOKEN, USER, is_staging_test
label_desc: Use image node_id 2 for calling the ModelTesterMixin obj's underlying member method code with example usage: obj.test_getattr_is_correct() without return types