code: def __init__(
      self,
      parent,
      batch_size=7,
      num_channels=3,
      image_size=18,
      min_resolution=30,
      max_resolution=400,
      do_resize=True,
      size=18,
      do_normalize=True,
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.num_channels = num_channels
      self.image_size = image_size
      self.min_resolution = min_resolution
      self.max_resolution = max_resolution
      self.do_resize = do_resize
      self.size = size
      self.do_normalize = do_normalize
  
imports: import json
  import os
  import tempfile
  import unittest
  import numpy
  from datasets import load_dataset
  from transformers.testing_utils import require_torch, require_vision, slow
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
label_desc: Use image node_id 1 to create a new ImageGPTFeatureExtractionTester object from inherited base classes: unittest with example: obj = ImageGPTFeatureExtractionTester(parent, batch_size, num_channels, image_size, min_resolution, max_resolution, do_resize, size, do_normalize)