code: def test_MLModel_warning(self):
      self.spec.specificationVersion = 3
      import warnings
  
      with warnings.catch_warnings(record=True) as w:
          # Cause all warnings to always be triggered.
          warnings.simplefilter("always")
          model = MLModel(self.spec)
          assert len(w) == 1
          assert issubclass(w[-1].category, RuntimeWarning)
          assert "not able to run predict()" in str(w[-1].message)
      self.spec.specificationVersion = 1
      model = MLModel(self.spec)
  
imports: import os
  import tempfile
  import unittest
  import numpy
  import PIL.Image
  import coremltools
  from coremltools import ComputeUnit
  from coremltools._deps import _HAS_TORCH
  from coremltools.converters.mil import Builder
  from coremltools.models import MLModel, datatypes
  from coremltools.models.neural_network import NeuralNetworkBuilder
  from coremltools.models.neural_network.utils import make_image_input, make_nn_classifier
  from coremltools.models.utils import _convert_neural_network_spec_weights_to_fp16, _is_macos, _macos_version, convert_double_to_float_multiarray_type, rename_feature, save_spec
  from coremltools.proto import Model_pb2
label_desc: Use image node_id 11 for calling the MLModelTest obj's underlying member method code with example usage: obj.test_MLModel_warning() without return types