code: def test_ldm_default_ddim(self):
      pipe = LDMTextToImagePipeline.from_pretrained(
          "CompVis/ldm-text2im-large-256"
      ).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, 256, 256, 3)
      expected_slice = np.array(
          [
              0.51825,
              0.52850,
              0.52543,
              0.54258,
              0.52304,
              0.52569,
              0.54363,
              0.55276,
              0.56878,
          ]
      )
      max_diff = np.abs(expected_slice - image_slice).max()
      assert max_diff < 1e-3
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNet2DConditionModel
  from diffusers.utils.testing_utils import enable_full_determinism, load_numpy, nightly, require_torch_gpu, torch_device
  from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineTesterMixin
label_desc: Use image node_id 3 for calling the LDMTextToImagePipelineSlowTests obj's underlying member method code with example usage: obj.test_ldm_default_ddim() without return types