1 def compute_accuracy(v_xs, v_ys): 2 global prediction 3 y_pre = sess.run(prediction, feed_dict={xs: v_xs, keep_prob: 1}) 4 correct_prediction = tf.equal(tf.argmax(y_pre,1), tf.argmax(v_ys,1)) 5 accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32)) 6 result = sess.run(accuracy, feed_dict={xs: v_xs, ys: v_ys, keep_prob: 1}) 7 return result