model_mnist.py 文件源码

def _create_summaries(self):
        base_summaries = tf.get_collection(tf.GraphKeys.SUMMARIES)
        with tf.name_scope('summaries/train'):
            train_loss = tf.summary.scalar('loss', self.loss)
            train_histo_loss = tf.summary.histogram(
                'histogram_loss', self.loss
            )
            train_summaries = [train_loss, train_histo_loss]
            train_summaries.extend(base_summaries)
            self.train_summary_op = tf.summary.merge(train_summaries)
        with tf.name_scope('summaries/valid'):
            valid_loss = tf.summary.scalar('loss', self.loss)
            valid_histo_loss = tf.summary.histogram(
                'histogram_loss', self.loss
            )
            valid_summaries = [valid_loss, valid_histo_loss]
            valid_summaries.extend(base_summaries)
            self.valid_summary_op = tf.summary.merge(valid_summaries)