def test_ngram_op_2_order(self):
''' test ngram 2-order op'''
ground_truth_2 = [0, 0, 0, 0, 0, 0, 0]
word_ngram = 2
t_input = tf.placeholder(shape=(4,), dtype=tf.int32)
t_ngram = py_x_ops.ngram(
t_input, word_ngrams=word_ngram, vocab_size=5000, bucket_size=100000)
logging.info("t_ngram: {}".format(t_ngram))
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
ngram_result = sess.run(t_ngram, feed_dict={t_input: self.testcase[0]})
self.assertAllEqual(ngram_result, ground_truth_2)
def test_batch_ngram_op_2_order(self):
''' tset batch 2-order ngram '''
ground_truth_2 = [[0, 0, 0, 0, 0, 0, 0], [223, 0, 0, 0, 0, 0, 0],
[0, 8, 5008, 0, 0, 0, 0], [4, 8, 102492, 0, 0, 0, 0],
[0, 0, 10, 5000, 5010, 0, 0],
[2, 5, 3, 103747, 51858, 0, 0],
[7, 2, 1, 24, 50599, 103743, 54395]]
word_ngram = 2
t_input = tf.placeholder(shape=(7, 4), dtype=tf.int32)
t_ngram = py_x_ops.ngram(
t_input, word_ngrams=word_ngram, vocab_size=5000, bucket_size=100000)
logging.info("batch t_ngram: {}".format(t_ngram))
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
ngram_result = sess.run(t_ngram, feed_dict={t_input: self.testcase})
ngram_result = [list(res) for res in ngram_result]
self.assertAllEqual(ngram_result, ground_truth_2)