Question

初学者并尝试在tensorflow prgm中使用tensorboard。我在教程中看到我添加了tensorboard refs，但是我收到以下错误消息：

InvalidArgumentError（请参阅上面的回溯）：您必须为占位符张量提供一个值＆＃39; x＆＃39;与dtype浮动 [[Node：x = Placeholderdtype = DT_FLOAT，shape = []，_device =＆＃34; / job：localhost / replica：0 / task：0 / cpu：0＆＃34;]]

错误似乎与我在训练循环中添加的这一行有关。没有这一行，程序不会抛出任何错误：

summary = sess.run(merged_summary_op, {x: x_train, y_prim: y_train})

感谢有人可以查看下面的代码并提供帮助：

# -*- coding: utf-8 -*-

import tensorflow as tf
sess = tf.Session()

# parms
a = tf.Variable([2.0], dtype=tf.float32, name="a")
x = tf.placeholder(tf.float32, name="x")
b = tf.Variable([1.0], dtype=tf.float32, name="b")

# model : y=ax+b
with tf.name_scope('Model'):
    y = tf.add ((tf.multiply(a, x)), b)

# info for TensorBoard 
writer = tf.summary.FileWriter("D:\\tmp\\tensorflow\\logs", sess.graph)

# loss fct - mean square error
with tf.name_scope('cost'):
    y_prim = tf.placeholder(tf.float32)
    cost = tf.reduce_sum(tf.square(y - y_prim))

# optimizer = gradientdescent
with tf.name_scope('GradDes'):
    optimizer = tf.train.GradientDescentOptimizer(0.01)
    train = optimizer.minimize(cost)

# train datas 
x_train = [1, 2, 3, 4]
y_train = [5.2, 8.4, 11.1, 14.7]

# summary for Tensorboard
tf.summary.scalar("cost", cost)
merged_summary_op = tf.summary.merge_all()

# init vars
init = tf.global_variables_initializer()

# train loop
sess.run(init)  
for i in range (500):
    sess.run([train, cost], feed_dict={x: x_train, y_prim: y_train})
    summary = sess.run(merged_summary_op, {x: x_train, y_prim: y_train})
    a_found, b_found, curr_cost = sess.run([a, b, cost], feed_dict={x:x_train, y_prim: y_train}) 
    print("iteration :", i, "a: ", a_found, "b: ", b_found, "cost: ",curr_cost)

Answer 1

不要在单独的sess.run中执行合并的摘要操作。试试这个：

a_found, b_found, curr_cost, summary = sess.run([a, b, cost, merged_summary_op], feed_dict={x:x_train, y_prim: y_train})

会话运行后，您需要调用FileWriter的add_summary方法：

writer.add_summary(summary)
writer.flush()

Answer 2

是的，我的代码也有同样的问题，我通过重置图形将其添加到图形定义的开头来解决了该问题

tf.reset_default_graph（）

我认为您做的一切正确

tensorflow tensorboard错误：您必须为占位符张量提供一个值

2 个答案: