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[0]
  
      expected_image = load_numpy(
          "https://huggingface.co/datasets/diffusers/test-arrays/resolve/main/ldm_text2img/ldm_large_256_ddim.npy"
      )
      max_diff = np.abs(expected_image - image).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 LDMTextToImagePipelineNightlyTests obj's underlying member method code with example usage: obj.test_ldm_default_ddim() without return types