def testPyramidalEncoderShortSequences(self):
sequence_length = [3, 4, 2]
inputs = tf.zeros([3, 4, 5])
encoder = encoders.PyramidalRNNEncoder(3, 10, reduction_factor=2)
outputs, state, encoded_length = encoder(
inputs, sequence_length=sequence_length)
encoded_length = self.evaluate(encoded_length)
self.assertAllEqual([1, 1, 1], encoded_length)
def testPyramidalEncoderShortSequences(self):
sequence_length = [3, 4, 2]
inputs = _build_dummy_sequences(sequence_length)
encoder = encoders.PyramidalRNNEncoder(3, 10, reduction_factor=2)
outputs, state, encoded_length = encoder.encode(
inputs, sequence_length=sequence_length)
with self.test_session() as sess:
sess.run(tf.global_variables_initializer())
encoded_length = sess.run(encoded_length)
self.assertAllEqual([1, 1, 1], encoded_length)
def testPyramidalEncoder(self):
sequence_length = [17, 21, 20]
inputs = tf.zeros([3, 21, 5])
encoder = encoders.PyramidalRNNEncoder(3, 10, reduction_factor=2)
outputs, state, encoded_length = encoder(
inputs, sequence_length=sequence_length)
self.assertEqual(3, len(state))
outputs, encoded_length = self.evaluate([outputs, encoded_length])
self.assertAllEqual([3, 6, 10], outputs.shape)
self.assertAllEqual([4, 5, 5], encoded_length)
def testPyramidalEncoder(self):
sequence_length = [17, 21, 20]
inputs = _build_dummy_sequences(sequence_length)
encoder = encoders.PyramidalRNNEncoder(3, 10, reduction_factor=2)
outputs, _, encoded_length = encoder.encode(
inputs, sequence_length=sequence_length)
with self.test_session() as sess:
sess.run(tf.global_variables_initializer())
outputs, encoded_length = sess.run([outputs, encoded_length])
self.assertAllEqual([3, 6, 10], outputs.shape)
self.assertAllEqual([4, 5, 5], encoded_length)
def testSequentialEncoder(self):
sequence_length = [17, 21, 20]
inputs = _build_dummy_sequences(sequence_length)
encoder = encoders.SequentialEncoder([
encoders.UnidirectionalRNNEncoder(1, 20),
encoders.PyramidalRNNEncoder(3, 10, reduction_factor=2)])
_, _, encoded_length = encoder.encode(
inputs, sequence_length=sequence_length)
with self.test_session() as sess:
sess.run(tf.global_variables_initializer())
encoded_length = sess.run(encoded_length)
self.assertAllEqual([4, 5, 5], encoded_length)
def testPyramidalEncoder(self):
sequence_length = [17, 21, 20]
inputs = _build_dummy_sequences(sequence_length)
encoder = encoders.PyramidalRNNEncoder(3, 10, reduction_factor=2)
outputs, state, encoded_length = encoder.encode(
inputs, sequence_length=sequence_length)
self.assertEqual(3, len(state))
for s in state:
self.assertIsInstance(s, tf.nn.rnn_cell.LSTMStateTuple)
with self.test_session() as sess:
sess.run(tf.global_variables_initializer())
outputs, encoded_length = sess.run([outputs, encoded_length])
self.assertAllEqual([3, 6, 10], outputs.shape)
self.assertAllEqual([4, 5, 5], encoded_length)
def testSequentialEncoder(self):
sequence_length = [17, 21, 20]
inputs = _build_dummy_sequences(sequence_length)
encoder = encoders.SequentialEncoder([
encoders.UnidirectionalRNNEncoder(1, 20),
encoders.PyramidalRNNEncoder(3, 10, reduction_factor=2)
])
_, state, encoded_length = encoder.encode(
inputs, sequence_length=sequence_length)
self.assertEqual(4, len(state))
for s in state:
self.assertIsInstance(s, tf.contrib.rnn.LSTMStateTuple)
with self.test_session() as sess:
sess.run(tf.global_variables_initializer())
encoded_length = sess.run(encoded_length)
self.assertAllEqual([4, 5, 5], encoded_length)
def __init__(self):
super(ListenAttendSpell, self).__init__(
source_inputter=inputters.SequenceRecordInputter(input_depth=40),
target_inputter=inputters.WordEmbedder(embedding_size=50),
encoder=encoders.PyramidalRNNEncoder(
num_layers=3,
num_units=512,
reduction_factor=2,
cell_class=tf.keras.layers.LSTMCell,
dropout=0.3),
decoder=decoders.AttentionalRNNDecoder(
num_layers=3,
num_units=512,
attention_mechanism_class=tfa.seq2seq.LuongMonotonicAttention,
cell_class=tf.keras.layers.LSTMCell,
dropout=0.3,
residual_connections=False,
first_layer_attention=True))
