code: def can_allow_multiple_input_shapes(spec):
      
  
      # First, check that the model actually has a neural network in it
      try:
          layers = _get_nn_layers(spec)
      except:
          raise Exception('Unable to verify that this model contains a neural network.')
  
      try:
          shaper = NeuralNetworkShaper(spec, False)
      except:
          raise Exception('Unable to compute shapes for this neural network.')
  
      inputs = _get_input_names(spec)
  
      for name in inputs:
  
          shape_dict = shaper.shape(name)
          shape = NeuralNetworkMultiArrayShapeRange(shape_dict)
  
          if (shape.isFlexible()):
              return True
  
      return False
docs: Examines a model specification and determines if it can compute results for more than one output shape.
  
      :param spec: MLModel
          The protobuf specification of the model.
  
      :return: Bool
          Returns True if the model can allow multiple input shapes, False otherwise.