code: def test_img2img_pndm(self):
      sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
          "runwayml/stable-diffusion-v1-5"
      )
      sd_pipe.to(torch_device)
      sd_pipe.set_progress_bar_config(disable=None)
  
      inputs = self.get_inputs(torch_device)
      image = sd_pipe(**inputs).images[0]
  
      expected_image = load_numpy(
          "https://huggingface.co/datasets/diffusers/test-arrays/resolve/main"
          "/stable_diffusion_img2img/stable_diffusion_1_5_pndm.npy"
      )
      max_diff = np.abs(expected_image - image).max()
      assert max_diff < 1e-3
  
imports: import gc
  import random
  import traceback
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, AutoencoderTiny, DDIMScheduler, DPMSolverMultistepScheduler, HeunDiscreteScheduler, LCMScheduler, LMSDiscreteScheduler, PNDMScheduler, StableDiffusionImg2ImgPipeline, UNet2DConditionModel
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_image, load_numpy, nightly, require_python39_or_higher, require_torch_2, require_torch_gpu, run_test_in_subprocess, skip_mps, slow, torch_device
  from ..pipeline_params import IMAGE_TO_IMAGE_IMAGE_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS, TEXT_TO_IMAGE_CALLBACK_CFG_PARAMS
  from ..test_pipelines_common import PipelineKarrasSchedulerTesterMixin, PipelineLatentTesterMixin, PipelineTesterMixin
label_desc: Use image node_id 3 for calling the StableDiffusionImg2ImgPipelineNightlyTests obj's underlying member method code with example usage: obj.test_img2img_pndm() without return types