def METHOD_NAME(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