code: def dummy_image(self):
      batch_size = 1
      num_channels = 3
      sizes = (32, 32)
  
      image = floats_tensor(
          (batch_size, num_channels) + sizes, rng=random.Random(0)
      ).to(torch_device)
      return image
  
file_path: llmga/llmga/diffusers/tests/pipelines/latent_diffusion/test_latent_diffusion_superresolution.py
imports: import random
  import unittest
  import numpy
  import torch
  from diffusers import DDIMScheduler, LDMSuperResolutionPipeline, UNet2DModel, VQModel
  from diffusers.utils import PIL_INTERPOLATION
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_image, nightly, require_torch, torch_device
label_desc: Use image node_id 1 for calling the LDMSuperResolutionPipelineFastTests obj's underlying member method code with example usage: obj.dummy_image() and returns: image