code: def test_predict_with_sarray(self):
      for index in range(len(self.models)):
          model = self.models[index]
          sf = self.trains[index]
          for output_type in ["class", "probability_vector"]:
              preds = model.predict(
                  sf[self.feature], output_type=output_type
              )
              if output_type == "class":
                  assert preds.dtype == sf[self.target].dtype
              else:
                  assert preds.dtype == _array
              assert len(preds) == len(sf)
  
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 17 for calling the DrawingClassifierTest obj's underlying member method code with example usage: obj.test_predict_with_sarray() without return types