Question

如何更改会话 for loop 内的张量流常量。
我是学习者，我想知道如何在for循环中更新它

import tensorflow as tf
import numpy as np

looperCount = 10

data = np.random.randint(2, size=looperCount)
x = tf.constant(data, name='x')

y = tf.Variable((5 * (x * x)) - (3 * x) + 15, name="y")
model = tf.initialize_all_variables()

with tf.Session() as sess:
    for i in range(looperCount):
        sess.run(model)
        data = np.random.randint(2, size=looperCount)
        x = tf.constant(data, name='x')
        avg = np.average(sess.run(y))
        print "avg - {}, sess - {}".format(avg, sess.run(y))

更新了工作代码

import tensorflow as tf
import numpy as np

looperCount = 10

x = tf.placeholder("float", looperCount)
y = (5 * (x * x)) - (3 * x) + 15

with tf.Session() as sess:
    for i in range(looperCount):
        data = np.random.randint(10, size=looperCount)
        result_y = sess.run(y, feed_dict={x: data})
        avg = np.average(result_y)
        print "avg - {:10} valy - {:10}".format("{:.2f}".format(avg), result_y)

Answer 1

在TensorFlow中，＆＃34;常数＆＃34;意思是：一旦你设置它，你就无法改变它。要更改TensorFlow程序在循环中使用的值，您有两个主要选择：（1）使用tf.placeholder()输入值，或（2）使用tf.Variable存储值在步骤之间，并tf.Variable.assign()更新它。

选项1更容易。以下是如何使用占位符来实现程序的示例：

import tensorflow as tf
import numpy as np

looperCount = 10

data = np.random.randint(2, size=looperCount)
x = tf.placeholder(tf.float64, shape=[2], name="x")

y = tf.Variable((5 * (x * x)) - (3 * x) + 15, name="y")
init_op = tf.initialize_all_variables()

with tf.Session() as sess:
    sess.run(init_op)      
    for i in range(looperCount):
        data = np.random.randint(2, size=looperCount)
        avg = np.average(sess.run(y, feed_dict={x: data}))
        print "avg - {}, sess - {}".format(avg, sess.run(y, feed_dict={x: data}))

循环时在tensoflow会话中更改常量

1 个答案: