code: def predict(self, feed_dict):
      is_train = "labels" in feed_dict
  
      for key in feed_dict.keys():
          feed_dict[key] = _utils.convert_shared_float_array_to_numpy(
              feed_dict[key]
          )
  
      feed_dict_for_session = {self.input: feed_dict["input"]}
  
      if is_train:
          feed_dict_for_session[self.labels] = feed_dict["labels"]
          feed_dict_for_session[self.weights] = feed_dict["weights"]
  
          pred_probs, loss = self.sess.run(
              [self.predictions, self.cost],
              feed_dict=feed_dict_for_session,
          )
  
          result = {
              "loss": _np.array(loss),
              "output": _np.array(pred_probs),
          }
      else:
          pred_probs = self.sess.run(
              [self.predictions], feed_dict=feed_dict_for_session
          )
          result = {"output": _np.array(pred_probs)}
  
      return result
  
file_path: turicreate/src/python/turicreate/toolkits/drawing_classifier/_tf_drawing_classifier.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import numpy
  from .._tf_model import TensorFlowModel
  import turicreate.toolkits._tf_utils
  from turicreate._deps.minimal_package import _minimal_package_import_check
label_desc: Use image node_id 5 for calling the DrawingClassifierTensorFlowModel obj's underlying member method code with example usage: obj.predict(feed_dict) and returns: result