code: def test_predict_output_type_probability_with_sarray(self):
      for index in range(len(self.models)):
          model = self.models[index]
          sf = self.trains[index]
          if len(sf[self.target].unique()) > 2:
              with self.assertRaises(_ToolkitError):
                  model.predict(
                      sf[self.feature], output_type="probability"
                  )
          else:
              preds = model.predict(
                  sf[self.feature], output_type="probability"
              )
              assert preds.dtype == float
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import os
  import turicreate
  from turicreate.toolkits._main import ToolkitError
  import numpy
  import tempfile
  from array import array
  import sys
  from .None import util
  import unittest
label_desc: Use image node_id 20 for calling the DrawingClassifierTest obj's underlying member method code with example usage: obj.test_predict_output_type_probability_with_sarray() without return types