code: def test_paint_by_example_inpaint(self):
      components = self.get_dummy_components()
  
      # make sure here that pndm scheduler skips prk
      pipe = PaintByExamplePipeline(**components)
      pipe = pipe.to("cpu")
      pipe.set_progress_bar_config(disable=None)
  
      inputs = self.get_dummy_inputs()
      output = pipe(**inputs)
      image = output.images
  
      image_slice = image[0, -3:, -3:, -1]
  
      assert image.shape == (1, 64, 64, 3)
      expected_slice = np.array(
          [
              0.4686,
              0.5687,
              0.4007,
              0.5218,
              0.5741,
              0.4482,
              0.4940,
              0.4629,
              0.4503,
          ]
      )
  
      assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
  
imports: import gc
  import random
  import unittest
  import numpy
  import torch
  from PIL import Image
  from transformers import CLIPImageProcessor, CLIPVisionConfig
  from diffusers import AutoencoderKL, PaintByExamplePipeline, PNDMScheduler, UNet2DConditionModel
  from diffusers.pipelines.paint_by_example import PaintByExampleImageEncoder
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_image, nightly, require_torch_gpu, torch_device
  from ..pipeline_params import IMAGE_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS, IMAGE_GUIDED_IMAGE_INPAINTING_PARAMS
  from ..test_pipelines_common import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the PaintByExamplePipelineFastTests obj's underlying member method code with example usage: obj.test_paint_by_example_inpaint() without return types