code: def test_model_from_pretrained(self):
      (
          init_dict,
          inputs_dict,
      ) = self.prepare_init_args_and_inputs_for_common()
  
      model = self.model_class(**init_dict)
      model.to(torch_device)
      model.eval()
  
      # test if the model can be loaded from the config
      # and has all the expected shape
      with tempfile.TemporaryDirectory() as tmpdirname:
          model.save_pretrained(tmpdirname, safe_serialization=False)
          new_model = self.model_class.from_pretrained(tmpdirname)
          new_model.to(torch_device)
          new_model.eval()
  
      # check if all parameters shape are the same
      for param_name in model.state_dict().keys():
          param_1 = model.state_dict()[param_name]
          param_2 = new_model.state_dict()[param_name]
          self.assertEqual(param_1.shape, param_2.shape)
  
      with torch.no_grad():
          output_1 = model(**inputs_dict)
  
          if isinstance(output_1, dict):
              output_1 = output_1.to_tuple()[0]
  
          output_2 = new_model(**inputs_dict)
  
          if isinstance(output_2, dict):
              output_2 = output_2.to_tuple()[0]
  
      self.assertEqual(output_1.shape, output_2.shape)
  
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 10 for calling the ModelTesterMixin obj's underlying member method code with example usage: obj.test_model_from_pretrained() without return types