InvalidArgumentError編碼時MNIST教程

Question

這些是我的第一個tensorflow步驟，我想如果別人有與我一樣的問題，如果有解決方法。

我編碼的MNIST教程和我當前的代碼段是：

#placeholder for input 
x = tf.placeholder(tf.float32,[None,784]) # None means a dimension can be of any length 

#Weights for the model: 784 pixel maps to ten results 
W = tf.Variable(tf.zeros([784,10])) 

#bias 
b = tf.Variable(tf.zeros([10])) 

#implementing the model 
y = tf.matmul(x,W) + b 

#implementing cross-entropy 
y_ = tf.placeholder(tf.float32,[None,10]) 

#cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1])) 
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.InteractiveSession() 
tf.global_variables_initializer().run() 

mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) 
for _ in range(1000): 
    batch_xs, batch_xy64 = mnist.train.next_batch(100) 
    batch_xy = batch_xy64.astype(np.float32) 
    sess.run(train_step , feed_dict={x:batch_xs,y:batch_xy}) 

correct_prediction = tf.equal(tf.argmax(y,1),tf.argmax(y_,1)) 
accuracy = tf.reduce_mean(tf.cast(correct_prediction,tf.float32)) 

print (sess.run(accuracy,feed_dict={x:mnist.test.images, y_:mnist.test.labels})) 

首先我從MNIST說明和一所提供的源代碼，這沒有什麼區別cross_entropy嘗試。

注意，我明確地嘗試施放batch_xy，因爲它是返回爲float 64

這也似乎是問題，因爲在session.run FLOAT32張量和變量似乎可以預料的。

至於我看到調試代碼，在MNIST的LABES返回爲float64 - 也許這說明我的錯誤：

 
... 
     File "/home/braunalx/python-workspace/LearnTensorFlow/firstSteps/MNIST_Start.py", line 40, in mnist_run 
    y_ = tf.placeholder(tf.float32,[None,10]) 


    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/array_ops.py", line 1548, in placeholder 
    return gen_array_ops._placeholder(dtype=dtype, shape=shape, name=name) 
... 
    InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10] 
    [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,10], _device="/job:localhost/replica:0/task:0/cpu:0"]()]] 

是否與所提供的數據MNIST什麼問題？

Answer 1

錯誤表示您沒有爲需要的佔位符提供值。在此行上替換y與y_sess.run(train_step , feed_dict={x:batch_xs,y:batch_xy})。