code: def test_stable_diffusion_1(self):
      sd_pipe = StableDiffusionKDiffusionPipeline.from_pretrained(
          "CompVis/stable-diffusion-v1-4"
      )
      sd_pipe = sd_pipe.to(torch_device)
      sd_pipe.set_progress_bar_config(disable=None)
  
      sd_pipe.set_scheduler("sample_euler")
  
      prompt = "A painting of a squirrel eating a burger"
      generator = torch.manual_seed(0)
      output = sd_pipe(
          [prompt],
          generator=generator,
          guidance_scale=9.0,
          num_inference_steps=20,
          output_type="np",
      )
  
      image = output.images
  
      image_slice = image[0, -3:, -3:, -1]
  
      assert image.shape == (1, 512, 512, 3)
      expected_slice = np.array(
          [
              0.0447,
              0.0492,
              0.0468,
              0.0408,
              0.0383,
              0.0408,
              0.0354,
              0.0380,
              0.0339,
          ]
      )
  
      assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
  
file_path: llmga/llmga/diffusers/tests/pipelines/stable_diffusion/test_stable_diffusion_k_diffusion.py
imports: import gc
  import unittest
  import numpy
  import torch
  from diffusers import StableDiffusionKDiffusionPipeline
  from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch_gpu, torch_device
label_desc: Use image node_id 2 for calling the StableDiffusionPipelineIntegrationTests obj's underlying member method code with example usage: obj.test_stable_diffusion_1() without return types