def test_sentence_encoder(self):
with self.assertRaises(Exception):
# pylint: disable=no-value-for-parameter
# on purpose, should fail
SentenceEncoder()
# pylint: enable=no-value-for-parameter
self._run_constructors(SentenceEncoder, SENTENCE_ENCODER_GOOD,
SENTENCE_ENCODER_BAD)
def test_save_and_load(self):
"""Try to save and load encoder."""
vocabulary = Vocabulary()
vocabulary.add_word("a")
vocabulary.add_word("b")
checkpoint_file = tempfile.NamedTemporaryFile(delete=False)
checkpoint_file.close()
encoder = SentenceEncoder(name="enc",
vocabulary=Vocabulary(),
data_id="data_id",
embedding_size=10,
rnn_size=20,
max_input_len=30,
save_checkpoint=checkpoint_file.name,
load_checkpoint=checkpoint_file.name)
encoder.input_sequence.register_input()
# NOTE: This assert needs to be here otherwise the model has
# no parameters since the sentence encoder is initialized lazily
self.assertIsInstance(encoder.temporal_states, tf.Tensor)
encoders_variables = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES,
scope="enc")
sess_1 = tf.Session()
sess_1.run(tf.global_variables_initializer())
encoder.save(sess_1)
sess_2 = tf.Session()
sess_2.run(tf.global_variables_initializer())
encoder.load(sess_2)
values_in_sess_1 = sess_1.run(encoders_variables)
values_in_sess_2 = sess_2.run(encoders_variables)
self.assertTrue(
all(
np.all(v1 == v2)
for v1, v2 in zip(values_in_sess_1, values_in_sess_2)))
os.remove(checkpoint_file.name)