def testRNMTPlusEncoder(self):
sequence_length = [4, 6, 5]
inputs = tf.zeros([3, 6, 5])
encoder = encoders.RNMTPlusEncoder(6, 10)
outputs, state, _ = encoder(inputs, sequence_length=sequence_length)
self.assertEqual(6, len(state))
self.assertEqual(10 * 2, tf.nest.flatten(state)[0].shape[-1])
outputs = self.evaluate(outputs)
self.assertAllEqual([3, max(sequence_length), 10], outputs.shape)
def testRNMTPlusEncoder(self):
sequence_length = [4, 6, 5]
inputs = _build_dummy_sequences(sequence_length)
encoder = encoders.RNMTPlusEncoder(6, 10)
outputs, state, _ = encoder.encode(inputs,
sequence_length=sequence_length)
self.assertEqual(6, len(state))
for s in state:
self.assertIsInstance(s, tf.nn.rnn_cell.LSTMStateTuple)
self.assertEqual(10 * 2, state[0].h.get_shape().as_list()[-1])
with self.test_session() as sess:
sess.run(tf.global_variables_initializer())
outputs = sess.run(outputs)
self.assertAllEqual([3, max(sequence_length), 10], outputs.shape)