callbacks.py 文件源码

def on_epoch_end(self, epoch, logs=None):
        logs = logs or {}

        if self.model.validation_data and self.histogram_freq:
            if epoch % self.histogram_freq == 0:
                # TODO: implement batched calls to sess.run
                # (current call will likely go OOM on GPU)
                if self.model.uses_learning_phase:
                    cut_v_data = len(self.model.inputs)
                    val_data = self.model.validation_data[:cut_v_data] + [0]
                    tensors = self.model.inputs + [K.learning_phase()]
                else:
                    val_data = self.model.validation_data
                    tensors = self.model.inputs
                feed_dict = dict(zip(tensors, val_data))
                result = self.sess.run([self.merged], feed_dict=feed_dict)
                summary_str = result[0]
                self.writer.add_summary(summary_str, epoch)

        for name, value in logs.items():
            if name in ['batch', 'size']:
                continue
            summary = tf.Summary()
            summary_value = summary.value.add()
            summary_value.simple_value = value.item()
            summary_value.tag = name
            self.writer.add_summary(summary, epoch)
        self.writer.flush()