Tensorflow Deep MNIST: Resource exhausted: OOM when allocating tensor with shape[10000,32,28,28]

Question

This is the sample MNIST code I am running:

from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets(\'MNIST_data\', one_         


        

Answer 1

Complementing Abhijay's answer, you can easily get the mean accuracy accross the test minibatches

accuracy_sum = tf.reduce_sum(tf.cast(correct_prediction, tf.float32))
good = 0
total = 0
for i in xrange(10):
    testSet = mnist.test.next_batch(50)
    good += accuracy_sum.eval(feed_dict={ x: testSet[0], y_: testSet[1], keep_prob: 1.0})
    total += testSet[0].shape[0]
print("test accuracy %g"%(good/total))