deepy/trainers/base.py
def _run_train(self, epoch, train_set, train_size=None):
        """
        Run one training iteration.
        """
        self.network.train_logger.record_epoch(epoch + 1)
        costs = self.train_step(train_set, train_size)
        if not epoch % self.config.monitor_frequency:
            self.report(dict(costs), "train", epoch)
        self.last_run_costs = costs
        return costs
def _run_train(self, epoch, train_set, train_size=None):
        """
        Run one training iteration.
        """
        self.network.train_logger.record_epoch(epoch + 1)
        costs = self.train_step(train_set, train_size)
        if not epoch % self.config.monitor_frequency:
            self.report(dict(costs), "train", epoch)
        self.last_run_costs = costs
        return costs
def _run_train ( self , epoch , train_set , train_size = None ) : self . network . train_logger . record_epoch ( epoch + 1 ) costs = self . train_step ( train_set , train_size ) if not epoch % self . config . monitor_frequency : self . report ( dict ( costs ) , "train" , epoch ) self . last_run_costs = costs return costs
Run one training iteration.
Run one training iteration .