code: def test_stable_diffusion_attention_slicing_v_pred(self):
      torch.cuda.reset_peak_memory_stats()
      model_id = "stabilityai/stable-diffusion-2"
      pipe = StableDiffusionPipeline.from_pretrained(
          model_id, torch_dtype=torch.float16
      )
      pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
  
      prompt = "a photograph of an astronaut riding a horse"
  
      # make attention efficient
      pipe.enable_attention_slicing()
      generator = torch.manual_seed(0)
      output_chunked = pipe(
          [prompt],
          generator=generator,
          guidance_scale=7.5,
          num_inference_steps=10,
          output_type="numpy",
      )
      image_chunked = output_chunked.images
  
      mem_bytes = torch.cuda.max_memory_allocated()
      torch.cuda.reset_peak_memory_stats()
      # make sure that less than 5.5 GB is allocated
      assert mem_bytes < 5.5 * 10**9
  
      # disable slicing
      pipe.disable_attention_slicing()
      generator = torch.manual_seed(0)
      output = pipe(
          [prompt],
          generator=generator,
          guidance_scale=7.5,
          num_inference_steps=10,
          output_type="numpy",
      )
      image = output.images
  
      # make sure that more than 3.0 GB is allocated
      mem_bytes = torch.cuda.max_memory_allocated()
      assert mem_bytes > 3 * 10**9
      max_diff = numpy_cosine_similarity_distance(
          image.flatten(), image_chunked.flatten()
      )
      assert max_diff < 1e-3
  
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 6 for calling the StableDiffusion2VPredictionPipelineIntegrationTests obj's underlying member method code with example usage: obj.test_stable_diffusion_attention_slicing_v_pred() without return types