code: def test_save_load(self):
      model_id = "hf-internal-testing/tiny-detr-mobilenetsv3-panoptic"
  
      model = AutoModelForImageSegmentation.from_pretrained(model_id)
      image_processor = AutoImageProcessor.from_pretrained(model_id)
      image_segmenter = pipeline(
          task="image-segmentation",
          model=model,
          image_processor=image_processor,
      )
      with tempfile.TemporaryDirectory() as tmpdirname:
          image_segmenter.save_pretrained(tmpdirname)
          pipeline(task="image-segmentation", model=tmpdirname)
  
imports: import tempfile
  import unittest
  from typing import Dict
  import datasets
  import numpy
  import requests
  from datasets import load_dataset
  from huggingface_hub.utils import insecure_hashlib
  from transformers import MODEL_FOR_IMAGE_SEGMENTATION_MAPPING, MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING, MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING, AutoImageProcessor, AutoModelForImageSegmentation, AutoModelForInstanceSegmentation, DetrForSegmentation, ImageSegmentationPipeline, MaskFormerForInstanceSegmentation, is_vision_available, pipeline
  from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_timm, require_torch, require_vision, slow
  from .test_pipelines_common import ANY
label_desc: Use image node_id 11 for calling the ImageSegmentationPipelineTests obj's underlying member method code with example usage: obj.test_save_load() without return types