def test_optimized_lstm_cell_matches_regular(self):
# Create regular LSTMCell.
rng = random.PRNGKey(0)
key1, key2 = random.split(rng)
x = random.normal(key1, (2, 3))
c0, h0 = nn.LSTMCell.initialize_carry(rng, (2, ), 4)
self.assertEqual(c0.shape, (2, 4))
self.assertEqual(h0.shape, (2, 4))
lstm = nn.LSTMCell()
(_, y), lstm_params = lstm.init_with_output(key2, (c0, h0), x)
# Create OptimizedLSTMCell.
rng = random.PRNGKey(0)
key1, key2 = random.split(rng)
x = random.normal(key1, (2, 3))
c0, h0 = nn.OptimizedLSTMCell.initialize_carry(rng, (2, ), 4)
self.assertEqual(c0.shape, (2, 4))
self.assertEqual(h0.shape, (2, 4))
lstm_opt = nn.OptimizedLSTMCell()
(_, y_opt), lstm_opt_params = lstm_opt.init_with_output(
key2, (c0, h0), x)
np.testing.assert_allclose(y, y_opt, rtol=1e-6)
jtu.check_eq(lstm_params, lstm_opt_params)
def __call__(self, carry, x):
return nn.OptimizedLSTMCell()(carry, x)
def __call__(self, carry, x):
for _ in range(self.n_layers):
carry, x = nn.OptimizedLSTMCell(activation_fn=self.activation_fn)(
carry, x)
return carry, x
