还原网络时,在还原的图形中找不到操作

使用tensorflow 1.9,我想在一个python文件中训练一个神经网络,然后使用另一个python文件恢复网络。我试图用一个简单的例子来实现这一点,但是当我试图加载“预测”操作时,我收到一个错误。具体来说,错误是: KeyError: "The name 'prediction' refers to an Operation not in the graph." .

下面是我用来训练和保存网络的python文件。它生成一些示例数据,训练一个简单的神经网络,然后保存网络的每个时代。

import numpy as np
import tensorflow as tf

input_data = np.zeros([100, 10])
label_data = np.zeros([100, 1])
for i in range(100):
    for j in range(10):
        input_data[i, j] = i * j / 1000
    label_data[i] = 2 * input_data[i, 0] + np.random.uniform(0.01)

input_placeholder = tf.placeholder(tf.float32, shape=[None, 10], name='input_placeholder')
label_placeholder = tf.placeholder(tf.float32, shape=[None, 1], name='label_placeholder')

x = tf.layers.dense(inputs=input_placeholder, units=10, activation=tf.nn.relu)
x = tf.layers.dense(inputs=x, units=10, activation=tf.nn.relu)
prediction = tf.layers.dense(inputs=x, units=1, name='prediction')

loss_op = tf.reduce_mean(tf.square(prediction - label_placeholder))
train_op = tf.train.AdamOptimizer(learning_rate=0.001).minimize(loss_op)

saver = tf.train.Saver()

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    for epoch_num in range(100):
        _, loss = sess.run([train_op, loss_op], feed_dict={input_placeholder: input_data, label_placeholder: label_data})
        print('epoch ' + str(epoch_num) + ', loss = ' + str(loss))
        saver.save(sess, '../Models/model', global_step=epoch_num + 1)

下面是我用来恢复网络的python文件。它加载输入和输出占位符,以及进行预测所需的操作。然而,即使我将一个操作命名为 prediction 在上面的培训代码中,下面的代码似乎无法在加载的图表中找到此操作。

import tensorflow as tf
import numpy as np

input_data = np.zeros([100, 10])
for i in range(100):
    for j in range(10):
        input_data[i, j] = i * j / 1000

with tf.Session() as sess:
    saver = tf.train.import_meta_graph('../Models/model-99.meta')
    saver.restore(sess, '../Models/model-99')
    graph = tf.get_default_graph()
    input_placeholder = graph.get_tensor_by_name('input_placeholder:0')
    label_placeholder = graph.get_tensor_by_name('label_placeholder:0')
    prediction = graph.get_operation_by_name('prediction')
    pred = sess.run([prediction], feed_dict={input_placeholder: input_data})

为什么此代码找不到此操作,我应该如何更正代码?