code: def test_save_pretrained_raise_not_implemented_exception(self):
      components = self.get_dummy_components()
      pipe = self.pipeline_class(**components)
      pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
      with tempfile.TemporaryDirectory() as tmpdir:
          try:
              # save_pretrained is not implemented for Multi-ControlNet
              pipe.save_pretrained(tmpdir)
          except NotImplementedError:
              pass
  
imports: import gc
  import tempfile
  import traceback
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, ControlNetModel, DDIMScheduler, EulerDiscreteScheduler, StableDiffusionControlNetPipeline, UNet2DConditionModel
  from diffusers.pipelines.controlnet.pipeline_controlnet import MultiControlNetModel
  from diffusers.utils.import_utils import is_xformers_available
  from diffusers.utils.testing_utils import enable_full_determinism, load_image, load_numpy, require_python39_or_higher, require_torch_2, require_torch_gpu, run_test_in_subprocess, slow, torch_device
  from diffusers.utils.torch_utils import randn_tensor
  from ..pipeline_params import IMAGE_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineKarrasSchedulerTesterMixin, PipelineLatentTesterMixin, PipelineTesterMixin
label_desc: Use image node_id 7 for calling the StableDiffusionMultiControlNetOneModelPipelineFastTests obj's underlying member method code with example usage: obj.test_save_pretrained_raise_not_implemented_exception() without return types