code: def test_stable_diffusion_inpaint_legacy_intermediate_state(self):
      number_of_steps = 0
  
      def callback_fn(
          step: int, timestep: int, latents: torch.FloatTensor
      ) -> None:
          callback_fn.has_been_called = True
          nonlocal number_of_steps
          number_of_steps += 1
          if step == 1:
              latents = latents.detach().cpu().numpy()
              assert latents.shape == (1, 4, 64, 64)
              latents_slice = latents[0, -3:, -3:, -1]
              expected_slice = np.array(
                  [
                      0.5977,
                      1.5449,
                      1.0586,
                      -0.3250,
                      0.7383,
                      -0.0862,
                      0.4631,
                      -0.2571,
                      -1.1289,
                  ]
              )
  
              assert (
                  np.abs(latents_slice.flatten() - expected_slice).max()
                  < 1e-3
              )
          elif step == 2:
              latents = latents.detach().cpu().numpy()
              assert latents.shape == (1, 4, 64, 64)
              latents_slice = latents[0, -3:, -3:, -1]
              expected_slice = np.array(
                  [
                      0.5190,
                      1.1621,
                      0.6885,
                      0.2424,
                      0.3337,
                      -0.1617,
                      0.6914,
                      -0.1957,
                      -0.5474,
                  ]
              )
  
              assert (
                  np.abs(latents_slice.flatten() - expected_slice).max()
                  < 1e-3
              )
  
      callback_fn.has_been_called = False
  
      pipe = StableDiffusionInpaintPipelineLegacy.from_pretrained(
          "CompVis/stable-diffusion-v1-4",
          safety_checker=None,
          torch_dtype=torch.float16,
      )
      pipe = pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
      pipe.enable_attention_slicing()
  
      inputs = self.get_inputs()
      pipe(**inputs, callback=callback_fn, callback_steps=1)
      assert callback_fn.has_been_called
      assert number_of_steps == 2
  
imports: import gc
  import random
  import unittest
  import numpy
  import torch
  from PIL import Image
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, DPMSolverMultistepScheduler, LMSDiscreteScheduler, PNDMScheduler, StableDiffusionInpaintPipelineLegacy, UNet2DConditionModel, UNet2DModel, VQModel
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_image, load_numpy, nightly, preprocess_image, require_torch_gpu, slow, torch_device
label_desc: Use image node_id 6 for calling the StableDiffusionInpaintLegacyPipelineSlowTests obj's underlying member method code with example usage: obj.test_stable_diffusion_inpaint_legacy_intermediate_state() without return types