code: def dummy_extractor(self):
      def extract(*args, **kwargs):
          class Out:
              def __init__(self):
                  self.pixel_values = torch.ones([0])
  
              def to(self, device):
                  self.pixel_values.to(device)
                  return self
  
          return Out()
  
      return extract
  
imports: import gc
  import random
  import unittest
  import numpy
  import torch
  from transformers import XLMRobertaTokenizer
  from diffusers import AltDiffusionImg2ImgPipeline, AutoencoderKL, PNDMScheduler, UNet2DConditionModel
  from diffusers.image_processor import VaeImageProcessor
  from diffusers.pipelines.alt_diffusion.modeling_roberta_series import RobertaSeriesConfig, RobertaSeriesModelWithTransformation
  from diffusers.utils import load_image
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_numpy, nightly, require_torch_gpu, torch_device
label_desc: Use image node_id 6 for calling the AltDiffusionImg2ImgPipelineFastTests obj's underlying member method code with example usage: obj.dummy_extractor() and returns: extract, Out, self