code: def test_metric_none(self):
      # Make sure that when passing in the reported_evaluation_metric as none, the model still works.
      #
  
      simple_data = self.data
      simple_train, simple_test = simple_data.random_split(0.8, seed=1)
  
      model = tc.boosted_trees_classifier.create(
          simple_train,
          target="label",
          disable_posttrain_evaluation=True,
      )
  
      # These fields should not be present.
      self.assertTrue(
          "training_confusion_matrix" not in model._list_fields()
      )
      self.assertTrue("training_precision" not in model._list_fields())
      self.assertTrue("training_recall" not in model._list_fields())
      self.assertTrue(
          "training_report_by_class" not in model._list_fields()
      )
  
      # None of these should error out.
      model.evaluate(simple_test)
      model.predict(simple_test)
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import turicreate
  import uuid
  import random
  import copy
  from turicreate.toolkits._main import ToolkitError
  import turicreate.toolkits.evaluation
  import shutil
  from array import array
  import os
label_desc: Use image node_id 16 for calling the BoostedTreesClassifierTest obj's underlying member method code with example usage: obj.test_metric_none() without return types