code: def test_export_coreml_with_predict(self):
      filename = tempfile.mkstemp("bingo.mlmodel")[1]
      self.model.export_coreml(filename)
  
      coreml_model = coremltools.models.MLModel(filename)
      img = self.sf[0:1][self.feature][0]
      img_fixed = tc.image_analysis.resize(
          img, *reversed(self.input_image_shape)
      )
      from PIL import Image
  
      pil_img = Image.fromarray(img_fixed.pixel_data)
  
      if _mac_ver() >= (10, 13):
          classes = self.model.classifier.classes
          ret = coreml_model.predict({self.feature: pil_img})
          coreml_values = [
              ret[self.target + "Probability"][l] for l in classes
          ]
  
          self.assertListAlmostEquals(
              coreml_values,
              list(
                  self.model.predict(
                      img_fixed, output_type="probability_vector"
                  )
              ),
              self.tolerance,
          )
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import os
  import sys
  import unittest
  import turicreate
  from turicreate.toolkits._main import ToolkitError
  from turicreate.toolkits._internal_utils import _mac_ver, _raise_error_if_not_sframe, _raise_error_if_not_sarray
  import tempfile
  import shutil
  import pytest
  import coremltools
  import platform
label_desc: Use image node_id 11 for calling the ImageClassifierTest obj's underlying member method code with example usage: obj.test_export_coreml_with_predict() without return types