code: def get_dummy_components(self):
      unet = self.dummy_unet
      movq = self.dummy_movq
  
      scheduler = DDIMScheduler(
          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=1,
          prediction_type="epsilon",
          thresholding=False,
      )
  
      components = {
          "unet": unet,
          "scheduler": scheduler,
          "movq": movq,
      }
      return components
  
imports: import gc
  import random
  import unittest
  import numpy
  import torch
  from diffusers import DDIMScheduler, KandinskyV22ControlnetPipeline, KandinskyV22PriorPipeline, UNet2DConditionModel, VQModel
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_image, load_numpy, nightly, require_torch_gpu, torch_device
  from ..test_pipelines_common import PipelineTesterMixin, assert_mean_pixel_difference
label_desc: Use image node_id 9 for calling the KandinskyV22ControlnetPipelineFastTests obj's underlying member method code with example usage: obj.get_dummy_components() and returns: components