def test_updates_algorithm(): n = shared_floatx(1) algorithm = UpdatesAlgorithm(updates=[(n, n + 1)]) algorithm.initialize() algorithm.process_batch({}) assert_allclose(n.get_value(), 2) algorithm.process_batch({}) assert_allclose(n.get_value(), 3)
def test_updates_algorithm(): n = shared_floatx(1) algorithm = UpdatesAlgorithm(updates=[(n, n + 1)]) algorithm.initialize() algorithm.process_batch({}) assert_allclose(n.get_value(), 2) algorithm.process_batch({}) assert_allclose(n.get_value(), 3)
def test_updates_algorithm_data(): n = shared_floatx(1) m = tensor.scalar('m') algorithm = UpdatesAlgorithm(updates=[(n, m + 1)]) algorithm.initialize() algorithm.process_batch({'m': 5}) assert_allclose(n.get_value(), 6) algorithm.process_batch({'m': 3}) assert_allclose(n.get_value(), 4)
def test_updates_algorithm_data(): n = shared_floatx(1) m = tensor.scalar('m') algorithm = UpdatesAlgorithm(updates=[(n, m + 1)]) algorithm.initialize() algorithm.process_batch({'m': 5}) assert_allclose(n.get_value(), 6) algorithm.process_batch({'m': 3}) assert_allclose(n.get_value(), 4)
def test_updates_algorithm_add_updates(): n = shared_floatx(1) m = shared_floatx(0) algorithm = UpdatesAlgorithm(updates=[(n, n + 1)]) algorithm.add_updates([(m, n % 2)]) assert len(algorithm.updates) == 2 algorithm.initialize() algorithm.process_batch({}) assert_allclose(n.get_value(), 2) assert_allclose(m.get_value(), 1) algorithm.process_batch({}) assert_allclose(n.get_value(), 3) assert_allclose(m.get_value(), 0)
def test_updates_algorithm_add_updates(): n = shared_floatx(1) m = shared_floatx(0) algorithm = UpdatesAlgorithm(updates=[(n, n + 1)]) algorithm.add_updates([(m, n % 2)]) assert len(algorithm.updates) == 2 algorithm.initialize() algorithm.process_batch({}) assert_allclose(n.get_value(), 2) assert_allclose(m.get_value(), 1) algorithm.process_batch({}) assert_allclose(n.get_value(), 3) assert_allclose(m.get_value(), 0)