mnist训练显存不足报错：Ran out of memory trying to allocate 957.03MiB. See logs for memory state. W tensorfl

参考：https://stackoverflow.com/questions/39076388/tensorflow-deep-mnist-resource-exhausted-oom-when-allocating-tensor-with-shape

训练mnist数据集，测试的时候报错，显存不足

解决办法：

（1）将

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

for i in xrange(10):
    testSet = mnist.test.next_batch(50)
    print("test accuracy %g"%accuracy.eval(feed_dict={ x: testSet[0], y_: testSet[1], keep_prob: 1.0}))

（2）改为

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))