code: def get_dummy_inputs(self, device, seed=0):
      if str(device).startswith("mps"):
          generator = torch.manual_seed(seed)
      else:
          generator = torch.Generator(device=device).manual_seed(seed)
      inputs = {
          "prompt": "A painting of a squirrel eating a burger",
          "generator": generator,
          "num_inference_steps": 2,
          "guidance_scale": 6.0,
          "output_type": "np",
          "width": 16,
          "height": 16,
      }
      return inputs
  
imports: import gc
  import unittest
  import numpy
  import torch
  from PIL import Image
  from transformers import AutoTokenizer, T5EncoderModel
  from diffusers import AutoPipelineForImage2Image, AutoPipelineForText2Image, Kandinsky3Pipeline, Kandinsky3UNet, VQModel
  from diffusers.image_processor import VaeImageProcessor
  from diffusers.schedulers.scheduling_ddpm import DDPMScheduler
  from diffusers.utils.testing_utils import enable_full_determinism, load_image, require_torch_gpu, slow
  from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_CALLBACK_CFG_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the Kandinsky3PipelineFastTests obj's underlying member method code with example usage: obj.get_dummy_inputs(device, seed) and returns: inputs