Tensorflow错误：无变量优化

我正在尝试在Tensorflow中实现神经网络。我正在使用tf.train.GradientDescentOptimizer来最小化熵。但是它显示了我的错误ValueError: No variables to optimizeTensorflow错误：无变量优化

下面是代码

import tensorflow as tf 
from tensorflow.examples.tutorials.mnist import input_data 
mnist = input_data.read_data_sets("MNIST_data/", one_hot = True) 

x = tf.placeholder(tf.float32,[None,748]) 
w = tf.zeros([748,10]) 
b = tf.zeros([10]) 
y = tf.matmul(x,w) + b 
y_ = tf.placeholder(tf.float32,[None,10]) 
cross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels = y_, logits = y)) 
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy) 

sess = tf.InteractiveSessoin() 
tf.global_variables_initializer().run() 

for i in range(1000): 
    batch_xs, batch_ys = mnist.train.next_batch(100) 
    sess.run(train_step, feed_dict = {x:batch_xs, y_:batch_ys})

我得到的错误是这样的

Traceback (most recent call last): 
    File "NeuralNetwork.py", line 15, in <module> 
    train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy) 
    File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/training/optimizer.py", line 193, in minimize 
    grad_loss=grad_loss) 
    File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/training/optimizer.py", line 244, in compute_gradients 
    raise ValueError("No variables to optimize") 
ValueError: No variables to optimize

来源

2017-03-16 Kavan

你不”有图中的任何变量进行优化。

w = tf.zeros([748,10]) 
b = tf.zeros([10])

应改为

w = tf.Variable(tf.zeros([748,10])) 
b = tf.Variable(tf.zeros([10]))

来源

2017-03-16 07:27:45 Himaprasoon

Himaprasoon是正确的！除此之外：零重量不会优化！将它们改为随机分布... – rmeertens

@rmeertens，那是不正确的。亚历山大， –

。它只是意味着变量被初始化为零。它仍然会优化（值会改变）。 – Himaprasoon

Tensorflow错误：无变量优化

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