在教程中发现TensorFlow错误
python
tensorflow
6
0

我敢问吗?目前,这是一项新技术,我找不到解决这种看似简单的错误的方法。我要阅读的教程可以在这里找到-http ://www.tensorflow.org/tutorials/mnist/pros/index.html#deep-mnist-for-experts

我从字面上复制了所有代码并将其粘贴到IPython Notebook中,在最后的代码块中出现错误。

# 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)

我以为我可能需要通过conda install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl安装或重新安装TensorFlow,但是conda甚至不知道如何安装。

有谁知道如何解决此错误?

参考资料:
Stack Overflow
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共 2 个回答
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我尝试一个简单的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,我将代码更改为以下代码,并且可以正常工作:

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

另一个解决方案是使用InteractiveSession。 InteractiveSession和Session之间的区别在于,InteractiveSession将自身设为默认会话,因此您无需显式调用该会话即可运行()或eval()。

v = tf.Variable(10, name="v")
sess = tf.InteractiveSession()
sess.run(v.initializer)
print(v.eval())
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我想到了。如您在值错误中看到的,它说No default session is registered. Use 'with DefaultSession(sess)' or pass an explicit session to eval(session=sess)所以我No default session is registered. Use 'with DefaultSession(sess)' or pass an explicit session to eval(session=sess)的答案是将显式会话传递给eval,就像它说的那样。这是我进行更改的地方。

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

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

现在代码可以正常工作了。

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