code: def test_stable_diffusion_default_ddim(self):
      pipe = StableDiffusionPipeline.from_pretrained(
          "stabilityai/stable-diffusion-2-base"
      )
      pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
  
      inputs = self.get_inputs(torch_device)
      image = pipe(**inputs).images
      image_slice = image[0, -3:, -3:, -1].flatten()
  
      assert image.shape == (1, 512, 512, 3)
      expected_slice = np.array(
          [
              0.49493,
              0.47896,
              0.40798,
              0.54214,
              0.53212,
              0.48202,
              0.47656,
              0.46329,
              0.48506,
          ]
      )
      assert np.abs(image_slice - expected_slice).max() < 7e-3
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, StableDiffusionPipeline, UNet2DConditionModel, logging
  from diffusers.utils.testing_utils import CaptureLogger, enable_full_determinism, load_numpy, nightly, numpy_cosine_similarity_distance, require_torch_gpu, slow, 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 3 for calling the StableDiffusion2PipelineSlowTests obj's underlying member method code with example usage: obj.test_stable_diffusion_default_ddim() without return types