code: def test_pickle(
      art_warning,
      image_dl_estimator,
      image_dl_estimator_defended,
      tmp_path,
  ):
      try:
          full_path = os.path.join(tmp_path, "my_classifier.p")
  
          classifier, _ = image_dl_estimator(functional=True)
          with open(full_path, "wb") as save_file:
              pickle.dump(classifier, save_file)
  
          with open(full_path, "rb") as load_file:
              loaded = pickle.load(load_file)
  
          assert (classifier._clip_values == loaded._clip_values).all()
          assert classifier._channels_first == loaded._channels_first
          if hasattr(classifier, "_use_logits"):
              assert classifier._use_logits == loaded._use_logits
          if hasattr(classifier, "_input_layer"):
              assert classifier._input_layer == loaded._input_layer
      except ARTTestException as e:
          art_warning(e)
  
imports: import logging
  import os
  from os import listdir, path
  import pickle
  import tempfile
  import keras
  import numpy
  import pytest
  from tensorflow.keras.callbacks import LearningRateScheduler
  from art.defences.preprocessor import FeatureSqueezing, JpegCompression, SpatialSmoothing
  from tests.utils import ARTTestException
label_desc: Use image node_id 7 for calling a global function with example usage: test_pickle(art_warning, image_dl_estimator, image_dl_estimator_defended, tmp_path) without return types