def test_run_lstm_cell(self):
filter_size = [3, 3]
output_size = [10, 10]
num_units = 15
state_name = 'lstm_state'
batch_size = 4
dtype = tf.float32
learned_state = False
inputs = tf.zeros([4, 10, 10, 3], dtype=tf.float32)
cell = lstm_cells.BottleneckConvLSTMCell(filter_size=filter_size,
output_size=output_size,
num_units=num_units)
init_state = cell.init_state(state_name, batch_size, dtype,
learned_state)
output, state_tuple = cell(inputs, init_state)
self.assertAllEqual([4, 10, 10, 15], output.shape.as_list())
self.assertAllEqual([4, 10, 10, 15], state_tuple[0].shape.as_list())
self.assertAllEqual([4, 10, 10, 15], state_tuple[1].shape.as_list())
def test_get_init_learned_state(self):
filter_size = [3, 3]
output_size = [10, 10]
num_units = 15
state_name = 'lstm_state'
batch_size = 4
dtype = tf.float32
learned_state = True
cell = lstm_cells.BottleneckConvLSTMCell(filter_size=filter_size,
output_size=output_size,
num_units=num_units)
init_c, init_h = cell.init_state(state_name, batch_size, dtype,
learned_state)
self.assertEqual(tf.float32, init_c.dtype)
self.assertEqual(tf.float32, init_h.dtype)
self.assertAllEqual([4, 10, 10, 15], init_c.shape.as_list())
self.assertAllEqual([4, 10, 10, 15], init_h.shape.as_list())
def test_get_init_state(self):
filter_size = [3, 3]
output_dim = 10
output_size = [output_dim] * 2
num_units = 15
state_name = 'lstm_state'
batch_size = 4
dtype = tf.float32
learned_state = False
cell = lstm_cells.BottleneckConvLSTMCell(filter_size=filter_size,
output_size=output_size,
num_units=num_units)
init_c, init_h = cell.init_state(state_name, batch_size, dtype,
learned_state)
self.assertEqual(tf.float32, init_c.dtype)
self.assertEqual(tf.float32, init_h.dtype)
with self.test_session() as sess:
init_c_res, init_h_res = sess.run([init_c, init_h])
self.assertAllClose(np.zeros((4, 10, 10, 15)), init_c_res)
self.assertAllClose(np.zeros((4, 10, 10, 15)), init_h_res)