Tf Summary 不提供直方图但保存会话图(预训练模型)

Tf Summary not giving the histograms but saves the session graph (pre-trained model)

我正在进行一项分析,以可视化在线提供的预训练模型的权重分布。它是在 CIFAR10 上训练的 Resnet18 模型。

我有以下代码从 metackpt 恢复模型,然后我尝试创建所有 weightsbias 的直方图使用 tf.summary.histogram

的卷积层
`with tf.Session(graph=tf.Graph()) as sess:
            read=tf.train.import_meta_graph(self.paths[0], clear_devices=True)
            try:
                read.restore(sess, tf.train.latest_checkpoint(self.paths[1]))
            except ValueError:
                try:
                    read.restore(sess, self.paths[1])
                except Exception as e:
                    print(e.message)

            # Summaries of weights
            summ_writer = tf.summary.FileWriter(self.sum_path, sess.graph)
            fp_summaries = []
            for lys in tf.trainable_variables():
                lay_nam = lys.name.split("/")[-2]
                if 'kernel' in lys.name:
                    with tf.name_scope(lay_nam+'_hist'):
                        tf_w_hist = tf.summary.histogram('Weights', tf.reshape(lys.eval(), [-1]))
                        fp_summaries.extend([tf_w_hist])
                if 'bias' in lys.name:
                    with tf.name_scope(lay_nam+'_hist'):
                        tf_b_hist = tf.summary.histogram('Bias', lys.eval())
                        fp_summaries.extend([tf_b_hist])
            tf_fp_summaries = tf.summary.merge(fp_summaries)
            # Run the graph
            output, _=sess.run([softmax, tf_fp_summaries], feed_dict={x: self.x_test[0:100, ]})

但是,文件夹中存储的日志事件仅存储主图。在 tensorboard 上看不到直方图。这里可能出了什么问题?

将合并的摘要节点传递给 sess.run 是不够的。您需要获取评估结果并将其传递给 FileWriter 实例的 add_summary 方法。

# evaluate the merged summary node in the graph
output, summ = sess.run([softmax, tf_fp_summaries], ...)
# explicitly write to file
summ_writer.add_summary(summ, global_step)
# optional, force to write to disk
summ_writer.flush()