I found a problem when you use tensorboard for visualization: if you define

MERGED = tf.summary.merge_ all();

After this operation, if you use it alone SESS.run ([merge]), the above error will be reported

At this point, you should work with other pigs instead SESS.run ([train, merged]), this error will not be reported again after the change

It’s hard for me to explain the specific reasons. Before, I checked this error for a long time and found some solutions, but none of them solved my problem

https://stackoverflow.com/questions/35114376/error-when-computing-summaries-in-tensorflow

Later, I referred to a GitHub program and changed it according to its appearance.

# -*- coding: utf-8 -*-
"""
Created on Wed Oct 31 17:07:38 2018

@author: LiZebin
"""

from __future__ import print_function
import numpy as np
import tensorflow as tf

tf.reset_default_graph()
SESS = tf.Session()

LOGDIR = "logs/"

X = np.arange(0, 1000, 2, dtype=np.float32)
Y = X*2.3+5.6
X_ = tf.placeholder(tf.float32, name="X")
Y_ = tf.placeholder(tf.float32, name="Y")
W = tf.get_variable(name="Weights", shape=[1],
                    dtype=tf.float32, initializer=tf.random_normal_initializer())
B = tf.get_variable(name="bias", shape=[1],
                    dtype=tf.float32, initializer=tf.random_normal_initializer())
PRED = W*X_+B
LOSS = tf.reduce_mean(tf.square(Y_-PRED))
tf.summary.scalar("Loss", LOSS)
TRAIN = tf.train.GradientDescentOptimizer(learning_rate=0.0000001).minimize(LOSS)
WRITER = tf.summary.FileWriter(LOGDIR, SESS.graph)
MERGED = tf.summary.merge_all()

SESS.run(tf.global_variables_initializer())
for step in range(20000):
    c1, c2, loss, RS, _ = SESS.run([W, B, LOSS, MERGED, TRAIN], feed_dict={X_:X, Y_:Y})   ####If you write RS=SESS.run(MERGED) after it alone, it will report the same error as before
    WRITER.add_summary(RS)
    if step%500 == 0:
        temp = "c1=%s, c2=%s, loss=%s"%(c1, c2, loss)
        print(temp)
SESS.close()