560cb94519ad5a5eed3adc323a9e1ad3cf0690e9,keras/callbacks.py,BaseLogger,on_batch_end,#BaseLogger#Any#Any#,120

Before Change

        batch_size = logs.get("size", 0)
        self.current += batch_size

        loss = logs.get("loss")
        self.log_values.append(("loss", loss))
        self.tot_loss += loss * batch_size
        if self.params["show_accuracy"]:
            accuracy = logs.get("accuracy")
            self.log_values.append(("acc.", accuracy))
            self.tot_acc += accuracy * batch_size
        // skip progbar update for the last batch; will be handled by on_epoch_end
        if self.verbose and self.current < self.params["nb_sample"]:
            self.progbar.update(self.current, self.log_values)

    def on_epoch_end(self, epoch, logs={}):

After Change

            self.log_values = []

    def on_batch_end(self, batch, logs={}):
        batch_size = logs.get("size", 0)
        self.seen += batch_size

        for k, v in logs.items():
            self.log_values.append((k, v))
            if k in self.totals:
                self.totals[k] += v * batch_size
            else:
                self.totals[k] = v * batch_size

        // skip progbar update for the last batch; will be handled by on_epoch_end
        if self.verbose and self.seen < self.params["nb_sample"]:
            self.progbar.update(self.seen, self.log_values)

    def on_epoch_end(self, epoch, logs={}):

Instances