code: def test_from_pipe_consistent(self):
      for (
          model_name,
          model_repo,
      ) in PRETRAINED_MODEL_REPO_MAPPING.items():
          if model_name in ["kandinsky", "kandinsky22"]:
              auto_pipes = [
                  AutoPipelineForText2Image,
                  AutoPipelineForImage2Image,
              ]
          else:
              auto_pipes = [
                  AutoPipelineForText2Image,
                  AutoPipelineForImage2Image,
                  AutoPipelineForInpainting,
              ]
  
          # test from_pretrained
          for pipe_from_class in auto_pipes:
              pipe_from = pipe_from_class.from_pretrained(
                  model_repo, variant="fp16", torch_dtype=torch.float16
              )
              pipe_from_config = dict(pipe_from.config)
  
              for pipe_to_class in auto_pipes:
                  pipe_to = pipe_to_class.from_pipe(pipe_from)
                  self.assertEqual(
                      dict(pipe_to.config), pipe_from_config
                  )
  
              del pipe_from, pipe_to
              gc.collect()
  
imports: import gc
  import os
  import shutil
  import unittest
  from collections import OrderedDict
  from pathlib import Path
  import torch
  from diffusers import AutoPipelineForImage2Image, AutoPipelineForInpainting, AutoPipelineForText2Image, ControlNetModel, DiffusionPipeline
  from diffusers.pipelines.auto_pipeline import AUTO_IMAGE2IMAGE_PIPELINES_MAPPING, AUTO_INPAINT_PIPELINES_MAPPING, AUTO_TEXT2IMAGE_PIPELINES_MAPPING
  from diffusers.utils.testing_utils import slow
label_desc: Use image node_id 2 for calling the AutoPipelineIntegrationTest obj's underlying member method code with example usage: obj.test_from_pipe_consistent() without return types