code: def test_stable_diffusion_text2img_intermediate_state_v_pred(self):
      number_of_steps = 0
  
      def test_callback_fn(
          step: int, timestep: int, latents: torch.FloatTensor
      ) -> None:
          test_callback_fn.has_been_called = True
          nonlocal number_of_steps
          number_of_steps += 1
          if step == 0:
              latents = latents.detach().cpu().numpy()
              assert latents.shape == (1, 4, 96, 96)
              latents_slice = latents[0, -3:, -3:, -1]
              expected_slice = np.array(
                  [
                      0.7749,
                      0.0325,
                      0.5088,
                      0.1619,
                      0.3372,
                      0.3667,
                      -0.5186,
                      0.6860,
                      1.4326,
                  ]
              )
  
              assert (
                  np.abs(latents_slice.flatten() - expected_slice).max()
                  < 5e-2
              )
          elif step == 19:
              latents = latents.detach().cpu().numpy()
              assert latents.shape == (1, 4, 96, 96)
              latents_slice = latents[0, -3:, -3:, -1]
              expected_slice = np.array(
                  [
                      1.3887,
                      1.0273,
                      1.7266,
                      0.0726,
                      0.6611,
                      0.1598,
                      -1.0547,
                      0.1522,
                      0.0227,
                  ]
              )
  
              assert (
                  np.abs(latents_slice.flatten() - expected_slice).max()
                  < 5e-2
              )
  
      test_callback_fn.has_been_called = False
  
      pipe = StableDiffusionPipeline.from_pretrained(
          "stabilityai/stable-diffusion-2", torch_dtype=torch.float16
      )
      pipe = pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
      pipe.enable_attention_slicing()
  
      prompt = "Andromeda galaxy in a bottle"
  
      generator = torch.manual_seed(0)
      pipe(
          prompt=prompt,
          num_inference_steps=20,
          guidance_scale=7.5,
          generator=generator,
          callback=test_callback_fn,
          callback_steps=1,
      )
      assert test_callback_fn.has_been_called
      assert number_of_steps == 20
  
imports: import gc
  import time
  import unittest
  import numpy
  import torch
  from huggingface_hub import hf_hub_download
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, DPMSolverMultistepScheduler, EulerDiscreteScheduler, StableDiffusionPipeline, UNet2DConditionModel
  from diffusers.models.attention_processor import AttnProcessor
  from diffusers.utils.testing_utils import enable_full_determinism, load_numpy, numpy_cosine_similarity_distance, require_torch_gpu, slow, torch_device
label_desc: Use image node_id 12 for calling the StableDiffusion2VPredictionPipelineIntegrationTests obj's underlying member method code with example usage: obj.test_stable_diffusion_text2img_intermediate_state_v_pred() without return types