code: def test_functional_model(art_warning, image_dl_estimator):
      try:
          # Need to update the functional_model code to produce a model with more than one input and output layers...
          classifier, _ = image_dl_estimator(
              functional=True, input_layer=1, output_layer=1
          )
          assert "input1" in classifier._input.name
          assert "output1" in classifier._output.name
  
          classifier, _ = image_dl_estimator(
              functional=True, input_layer=0, output_layer=0
          )
          assert "input0" in classifier._input.name
          assert "output0" in classifier._output.name
      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 8 for calling a global function with example usage: test_functional_model(art_warning, image_dl_estimator) without return types