code: def summary(self):
          
          if self.hasSummary:
              if self.numClasses <= 2:
                  return BinaryLogisticRegressionTrainingSummary(super(LogisticRegressionModel,
                                                                       self).summary)
              else:
                  return LogisticRegressionTrainingSummary(super(LogisticRegressionModel,
                                                                 self).summary)
          else:
              raise RuntimeError("No training summary available for this %s" %
                                 self.__class__.__name__)
docs: Gets summary (e.g. accuracy/precision/recall, objective history, total iterations) of model
          trained on the training set. An exception is thrown if `trainingSummary is None`.