code: def test_image_embeds_none(self):
      device = "cpu"  # ensure determinism for the device-dependent torch.Generator
      components = self.get_dummy_components()
      sd_pipe = StableUnCLIPImg2ImgPipeline(**components)
      sd_pipe = sd_pipe.to(device)
      sd_pipe.set_progress_bar_config(disable=None)
  
      inputs = self.get_dummy_inputs(device)
      inputs.update({"image_embeds": None})
      image = sd_pipe(**inputs).images
      image_slice = image[0, -3:, -3:, -1]
  
      assert image.shape == (1, 32, 32, 3)
      expected_slice = np.array(
          [
              0.3872,
              0.7224,
              0.5601,
              0.4741,
              0.6872,
              0.5814,
              0.4636,
              0.3867,
              0.5078,
          ]
      )
  
      assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
  
imports: import gc
  import random
  import unittest
  import numpy
  import torch
  from transformers import CLIPImageProcessor, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, CLIPVisionConfig, CLIPVisionModelWithProjection
  from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableUnCLIPImg2ImgPipeline, UNet2DConditionModel
  from diffusers.pipelines.pipeline_utils import DiffusionPipeline
  from diffusers.pipelines.stable_diffusion.stable_unclip_image_normalizer import StableUnCLIPImageNormalizer
  from diffusers.utils.import_utils import is_xformers_available
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_image, load_numpy, nightly, require_torch_gpu, skip_mps, torch_device
  from ..pipeline_params import TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS
  from ..test_pipelines_common import PipelineKarrasSchedulerTesterMixin, PipelineLatentTesterMixin, PipelineTesterMixin, assert_mean_pixel_difference
label_desc: Use image node_id 3 for calling the StableUnCLIPImg2ImgPipelineFastTests obj's underlying member method code with example usage: obj.test_image_embeds_none() without return types