def testBasicRNNCell(self):
with self.test_session() as sess:
with tf.variable_scope("root", initializer=tf.constant_initializer(0.5)):
x = tf.zeros([1, 2])
m = tf.zeros([1, 2])
my_cell = functools.partial(basic_rnn_cell, num_units=2)
# pylint: disable=protected-access
g, _ = rnn_cell_impl._SlimRNNCell(my_cell)(x, m)
# pylint: enable=protected-access
sess.run([tf.global_variables_initializer()])
res = sess.run([g], {x.name: np.array([[1., 1.]]),
m.name: np.array([[0.1, 0.1]])})
self.assertEqual(res[0].shape, (1, 2))
def testBasicRNNCell(self):
with self.test_session() as sess:
with variable_scope.variable_scope(
"root", initializer=init_ops.constant_initializer(0.5)):
x = array_ops.zeros([1, 2])
m = array_ops.zeros([1, 2])
my_cell = functools.partial(basic_rnn_cell, num_units=2)
# pylint: disable=protected-access
g, _ = rnn_cell_impl._SlimRNNCell(my_cell)(x, m)
# pylint: enable=protected-access
sess.run([variables_lib.global_variables_initializer()])
res = sess.run(
[g], {x.name: np.array([[1., 1.]]),
m.name: np.array([[0.1, 0.1]])})
self.assertEqual(res[0].shape, (1, 2))
def testBasicRNNCellMatch(self):
batch_size = 32
input_size = 100
num_units = 10
with self.test_session() as sess:
with tf.variable_scope("root", initializer=tf.constant_initializer(0.5)):
inputs = tf.random_uniform((batch_size, input_size))
_, initial_state = basic_rnn_cell(inputs, None, num_units)
my_cell = functools.partial(basic_rnn_cell, num_units=num_units)
# pylint: disable=protected-access
slim_cell = rnn_cell_impl._SlimRNNCell(my_cell)
# pylint: enable=protected-access
slim_outputs, slim_state = slim_cell(inputs, initial_state)
rnn_cell = tf.nn.rnn_cell.BasicRNNCell(num_units)
tf.get_variable_scope().reuse_variables()
outputs, state = rnn_cell(inputs, initial_state)
self.assertEqual(slim_outputs.get_shape(), outputs.get_shape())
self.assertEqual(slim_state.get_shape(), state.get_shape())
sess.run([tf.global_variables_initializer()])
res = sess.run([slim_outputs, slim_state, outputs, state])
self.assertAllClose(res[0], res[2])
self.assertAllClose(res[1], res[3])
def testBasicRNNCellMatch(self):
batch_size = 32
input_size = 100
num_units = 10
with self.test_session() as sess:
with variable_scope.variable_scope(
"root", initializer=init_ops.constant_initializer(0.5)):
inputs = random_ops.random_uniform((batch_size, input_size))
_, initial_state = basic_rnn_cell(inputs, None, num_units)
rnn_cell = rnn_cell_impl.BasicRNNCell(num_units)
outputs, state = rnn_cell(inputs, initial_state)
variable_scope.get_variable_scope().reuse_variables()
my_cell = functools.partial(basic_rnn_cell, num_units=num_units)
# pylint: disable=protected-access
slim_cell = rnn_cell_impl._SlimRNNCell(my_cell)
# pylint: enable=protected-access
slim_outputs, slim_state = slim_cell(inputs, initial_state)
self.assertEqual(slim_outputs.get_shape(), outputs.get_shape())
self.assertEqual(slim_state.get_shape(), state.get_shape())
sess.run([variables_lib.global_variables_initializer()])
res = sess.run([slim_outputs, slim_state, outputs, state])
self.assertAllClose(res[0], res[2])
self.assertAllClose(res[1], res[3])
