code: def get_dummy_components(self):
      unet = self.dummy_unet
      movq = self.dummy_movq
  
      ddim_config = {
          "num_train_timesteps": 1000,
          "beta_schedule": "linear",
          "beta_start": 0.00085,
          "beta_end": 0.012,
          "clip_sample": False,
          "set_alpha_to_one": False,
          "steps_offset": 0,
          "prediction_type": "epsilon",
          "thresholding": False,
      }
  
      scheduler = DDIMScheduler(**ddim_config)
  
      components = {
          "unet": unet,
          "scheduler": scheduler,
          "movq": movq,
      }
  
      return components
  
imports: import gc
  import random
  import unittest
  import numpy
  import torch
  from PIL import Image
  from diffusers import DDIMScheduler, KandinskyV22Img2ImgPipeline, KandinskyV22PriorPipeline, UNet2DConditionModel, VQModel
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_image, load_numpy, require_torch_gpu, slow, torch_device
  from ..test_pipelines_common import PipelineTesterMixin, assert_mean_pixel_difference
label_desc: Use image node_id 9 for calling the Dummies obj's underlying member method code with example usage: obj.get_dummy_components() and returns: components