code: def test_rai_insights_large_images_save_load_save(self):
      PIL.Image.MAX_IMAGE_PIXELS = None
      data = load_flowers_dataset(upscale=True)
      model = create_dummy_model(data)
      test = data
      class_names = data[ImageColumns.LABEL.value].unique()
      task_type = ModelTask.IMAGE_CLASSIFICATION
      label = ImageColumns.LABEL
      serializer = DummyFlowersPipelineSerializer()
  
      image_width = 2
      run_and_validate_serialization(
          model,
          test,
          task_type,
          class_names,
          label,
          serializer,
          image_width,
      )
  
imports: import shutil
  from pathlib import Path
  from tempfile import TemporaryDirectory
  from unittest.mock import patch
  import numpy
  import PIL
  import pytest
  from common_vision_utils import DummyFlowersPipelineSerializer, ImageClassificationPipelineSerializer, ObjectDetectionPipelineSerializer, create_dummy_model, create_image_classification_pipeline, load_flowers_dataset, load_fridge_object_detection_dataset, load_imagenet_dataset, load_imagenet_labels, retrieve_fridge_object_detection_model
  from rai_vision_insights_validator import run_and_validate_serialization
  from responsibleai_vision import ModelTask, RAIVisionInsights
  from responsibleai_vision.common.constants import ImageColumns
label_desc: Use image node_id 2 for calling the TestRAIVisionInsightsSaveAndLoadScenarios obj's underlying member method code with example usage: obj.test_rai_insights_large_images_save_load_save() without return types