code: def test_nudity_safetychecker_safe_stable_diffusion(self):
      sd_pipe = StableDiffusionPipeline.from_pretrained(
          "runwayml/stable-diffusion-v1-5"
      )
      sd_pipe = sd_pipe.to(torch_device)
      sd_pipe.set_progress_bar_config(disable=None)
  
      prompt = (
          "the four horsewomen of the apocalypse, painting by tom of finland, gaston bussiere, craig mullins, j. c."
          " leyendecker"
      )
      seed = 1044355234
      guidance_scale = 12
  
      generator = torch.manual_seed(seed)
      output = sd_pipe(
          [prompt],
          generator=generator,
          guidance_scale=guidance_scale,
          num_inference_steps=50,
          output_type="np",
          width=512,
          height=512,
          sld_guidance_scale=0,
      )
  
      image = output.images
      image_slice = image[0, -3:, -3:, -1]
      expected_slice = np.array(
          [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
      )
  
      assert image.shape == (1, 512, 512, 3)
  
      assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-7
  
      generator = torch.manual_seed(seed)
      output = sd_pipe(
          [prompt],
          generator=generator,
          guidance_scale=guidance_scale,
          num_inference_steps=50,
          output_type="np",
          width=512,
          height=512,
          sld_guidance_scale=2000,
          sld_warmup_steps=7,
          sld_threshold=0.025,
          sld_momentum_scale=0.5,
          sld_mom_beta=0.7,
      )
  
      image = output.images
      image_slice = image[0, -3:, -3:, -1]
      expected_slice = np.array(
          [
              0.5818,
              0.6285,
              0.6835,
              0.6019,
              0.625,
              0.6754,
              0.6096,
              0.6334,
              0.6561,
          ]
      )
      assert image.shape == (1, 512, 512, 3)
  
      assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
  
imports: import gc
  import random
  import tempfile
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNet2DConditionModel
  from diffusers.pipelines.stable_diffusion_safe import StableDiffusionPipelineSafe
  from diffusers.utils.testing_utils import floats_tensor, nightly, require_torch_gpu, torch_device
label_desc: Use image node_id 4 for calling the SafeDiffusionPipelineIntegrationTests obj's underlying member method code with example usage: obj.test_nudity_safetychecker_safe_stable_diffusion() without return types