在教程中发现TensorFlow错误

Question

敢问我甚么？在这一点上，这是一项新技术，我无法找到解决这个看似简单的错误的方法。我要去的教程可以在这里找到 - http://www.tensorflow.org/tutorials/mnist/pros/index.html#deep-mnist-for-experts

我将字面上的所有代码复制并粘贴到IPython Notebook中，并在最后一块代码中出现错误。

# To train and evaluate it we will use code that is nearly identical to that for the simple one layer SoftMax network above. 
# The differences are that: we will replace the steepest gradient descent optimizer with the more sophisticated ADAM optimizer. 

cross_entropy = -tf.reduce_sum(y_*tf.log(y_conv)) 
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy) 
correct_prediction = tf.equal(tf.argmax(y_conv,1), tf.argmax(y_,1)) 
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float")) 
sess.run(tf.initialize_all_variables()) 
for i in range(20000): 
    batch = mnist.train.next_batch(50) 
    if i%100 == 0: 
     train_accuracy = accuracy.eval(feed_dict={x:batch[0], y_: batch[1], keep_prob: 1.0}) 
    print "step %d, training accuracy %g"%(i, train_accuracy) 
    train_step.run(feed_dict={x: batch[0], y_: batch[1], keep_prob: 0.5}) 

print "test accuracy %g"%accuracy.eval(feed_dict={ 
    x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}) 

运行此代码后，我收到此错误。

--------------------------------------------------------------------------- 
ValueError        Traceback (most recent call last) 
<ipython-input-46-a5d1ab5c0ca8> in <module>() 
    15 
    16 print "test accuracy %g"%accuracy.eval(feed_dict={ 
---> 17  x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}) 

/root/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.pyc in eval(self, feed_dict, session) 
    403 
    404  """ 
--> 405  return _eval_using_default_session(self, feed_dict, self.graph, session) 
    406 
    407 

/root/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.pyc in _eval_using_default_session(tensors, feed_dict, graph, session) 
    2712  session = get_default_session() 
    2713  if session is None: 
-> 2714  raise ValueError("Cannot evaluate tensor using eval(): No default " 
    2715      "session is registered. Use 'with " 
    2716      "DefaultSession(sess)' or pass an explicit session to " 

ValueError: Cannot evaluate tensor using eval(): No default session is registered. Use 'with DefaultSession(sess)' or pass an explicit session to eval(session=sess) 

我认为我可能需要安装或通过畅达重新安装TensorFlow安装https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl但畅达甚至不知道如何安装它。

有没有人有任何想法如何解决这个错误？

Answer 1

我想通了。正如你在价值错误中看到的那样，它表示No default session is registered. Use 'with DefaultSession(sess)' or pass an explicit session to eval(session=sess)，所以我提出的答案是将显式会话传递给eval，就像它说的那样。这是我做出改变的地方。

if i%100 == 0: 
     train_accuracy = accuracy.eval(session=sess, feed_dict={x:batch[0], y_: batch[1], keep_prob: 1.0}) 

而且

train_step.run(session=sess, feed_dict={x: batch[0], y_: batch[1], keep_prob: 0.5}) 

现在代码工作正常。

Answer 2

我尝试了一个简单的tensorflow示例时遇到了类似的错误。

import tensorflow as tf 
v = tf.Variable(10, name="v") 
sess = tf.Session() 
sess.run(v.initializer) 
print(v.eval()) 

我的解决方案是使用sess.as_default（）。例如，我改变了我的代码下面，它的工作：

import tensorflow as tf 
v = tf.Variable(10, name="v") 
with tf.Session().as_default() as sess: 
    sess.run(v.initializer)  
    print(v.eval()) 

另一种解决方案可以使用InteractiveSession。 InteractiveSession和Session之间的区别在于InteractiveSession使其成为默认会话，因此您可以在不显式调用会话的情况下运行（）或eval（）。

v = tf.Variable(10, name="v") 
sess = tf.InteractiveSession() 
sess.run(v.initializer) 
print(v.eval())