def smoke_test(self):
""" A simple smoke test with random initialization"""
input_size = 4
input_length = 4
batch_size = 2
n_units = 4
cell = ESNCell(n_units)
inputs = np.random.random([input_length, batch_size, input_size])
state = cell.zero_state(batch_size, tf.float64)
for i in range(input_length):
if i > 0: tf.get_variable_scope().reuse_variables()
state, _ = cell(inputs[i, :, :], state)
with self.test_session() as sess:
sess.run(tf.global_variables_initializer())
final_states = sess.run(state)
expected_final_states = [[
-0.56735968, -0.21625957, 0.69647415, -0.91361383
], [-0.22654705, -0.15751715, 0.85077971, -0.89757621]]
self.assertAllClose(final_states, expected_final_states)
def test_esn_dynamics(self):
""" A simple smoke test """
input_size = 4
input_length = 4
batch_size = 2
n_units = 4
cell = ESNCell(n_units)
inputs = np.random.random([input_length, batch_size, input_size])
state = cell.zero_state(batch_size, tf.float64)
for i in range(input_length):
if i > 0: tf.get_variable_scope().reuse_variables()
state, _ = cell(inputs[i, :, :], state)
with self.test_session() as sess:
sess.run(tf.initialize_all_variables())
final_states = sess.run([state])
expected_final_states = [[[
0.75952783, -0.96463442, 0.72289173, 0.38016839
], [0.82451594, -0.99358452, 0.86248011, 0.24540841]]]
self.assertAllClose(final_states, expected_final_states)