code: def test_stable_diffusion_text2img_pipeline_v_pred_default(self):
      expected_image = load_numpy(
          "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/"
          "sd2-text2img/astronaut_riding_a_horse_v_pred.npy"
      )
  
      pipe = StableDiffusionPipeline.from_pretrained(
          "stabilityai/stable-diffusion-2"
      )
      pipe.to(torch_device)
      pipe.enable_attention_slicing()
      pipe.set_progress_bar_config(disable=None)
  
      prompt = "astronaut riding a horse"
  
      generator = torch.manual_seed(0)
      output = pipe(
          prompt=prompt,
          guidance_scale=7.5,
          generator=generator,
          output_type="np",
      )
      image = output.images[0]
  
      assert image.shape == (768, 768, 3)
      max_diff = numpy_cosine_similarity_distance(
          image.flatten(), expected_image.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 7 for calling the StableDiffusion2VPredictionPipelineIntegrationTests obj's underlying member method code with example usage: obj.test_stable_diffusion_text2img_pipeline_v_pred_default() without return types