def end_epoch()

in src/trainer.py [0:0]

• 22 lines of code
• 8 McCabe index (conditional complexity)

    def end_epoch(self, scores):
        """
        End the epoch.
        """
        # stop if the stopping criterion has not improved after a certain number of epochs
        if self.stopping_criterion is not None:
            metric, biggest = self.stopping_criterion
            assert metric in scores, metric
            factor = 1 if biggest else -1
            if factor * scores[metric] > factor * self.best_stopping_criterion:
                self.best_stopping_criterion = scores[metric]
                logger.info("New best validation score: %f" % self.best_stopping_criterion)
                self.decrease_counts = 0
            else:
                logger.info("Not a better validation score (%i / %i)."
                            % (self.decrease_counts, self.decrease_counts_max))
                self.decrease_counts += 1
            if self.decrease_counts > self.decrease_counts_max:
                logger.info("Stopping criterion has been below its best value for more "
                            "than %i epochs. Ending the experiment..." % self.decrease_counts_max)
                exit()

        for k in self.stats.keys():
            if type(self.stats[k]) is list:
                del self.stats[k][:]

        self.save_checkpoint()
        self.epoch += 1