def test(sess, cnn, testList, merged):
label = []
sum_pair = 0
for i in numbertest:
sum_pair += i
for line in testList:
label_item = int(line[0])
label.append(label_item)
x_test_1, x_test_2, x_test_3 = data_helper.load_val_batch(
testList, vocab, 0, sum_pair)
feed_dict = {
cnn.input_x_1: x_test_1,
cnn.input_x_2: x_test_2, # x_test_2 equals x_test_3 for the test case
cnn.lengths: x_test_3,
cnn.label: np.array(label)
}
summary, acc = sess.run([merged, cnn.accuracy], feed_dict)
return summary, acc
def dev_step(sess, cnn, testList):
ndcg3 = []
ndcg5 = []
ndcg10 = []
ndcg20 = []
sum1 = 0
for i in numbertest:
queryList = []
x_test_1, x_test_2, x_test_3 = data_helper.load_val_batch(
testList, vocab, sum1, i)
feed_dict = {
cnn.input_x_1: x_test_1,
cnn.input_x_2:
x_test_2, # x_test_2 equals x_test_3 for the test case
cnn.lengths: x_test_3
}
predicted = sess.run(cnn.score, feed_dict)
for index, s in enumerate(predicted):
line = testList[sum1 + index]
term = line[0]
queryList.append((term, predicted[index]))
sum1 += i
queryList = sorted(queryList, key=lambda x: x[1])
queryList.reverse()
query_sort = [int(x[0]) for x in queryList]
r = []
for j in query_sort:
r.append(j)
ndcg3.append(ndcg_at_k(r, 3))
ndcg5.append(ndcg_at_k(r, 5))
ndcg10.append(ndcg_at_k(r, 10))
ndcg20.append(ndcg_at_k(r, 20))
return sum(ndcg3) * 1.0 / len(ndcg3), sum(ndcg5) * 1.0 / len(
ndcg5), sum(ndcg10) * 1.0 / len(ndcg10), sum(ndcg20) * 1.0 / len(
ndcg20)