code: def test_stable_diffusion_model_editing_pndm(self):
      device = "cpu"  # ensure determinism for the device-dependent torch.Generator
      components = self.get_dummy_components()
      components["scheduler"] = PNDMScheduler()
      sd_pipe = StableDiffusionModelEditingPipeline(**components)
      sd_pipe = sd_pipe.to(device)
      sd_pipe.set_progress_bar_config(disable=None)
  
      inputs = self.get_dummy_inputs(device)
      # the pipeline does not expect pndm so test if it raises error.
      with self.assertRaises(ValueError):
          _ = sd_pipe(**inputs).images
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, PNDMScheduler, StableDiffusionModelEditingPipeline, UNet2DConditionModel
  from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch_gpu, skip_mps, torch_device
  from ..pipeline_params import 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 6 for calling the StableDiffusionModelEditingPipelineFastTests obj's underlying member method code with example usage: obj.test_stable_diffusion_model_editing_pndm() without return types