def test_keys(self): # A regression test to make sure issue #49 does no longer pop up. By # iterating over the configuration in the for loop, it should not raise # a KeyError if the child hyperparameter is inactive. cs = ConfigurationSpace() shrinkage = CategoricalHyperparameter( "shrinkage", ["None", "auto", "manual"], default_value="None", ) shrinkage_factor = UniformFloatHyperparameter( "shrinkage_factor", 0., 1., 0.5, ) cs.add_hyperparameters([shrinkage, shrinkage_factor]) cs.add_condition(EqualsCondition(shrinkage_factor, shrinkage, "manual")) for i in range(10): config = cs.sample_configuration() d = { hp_name: config[hp_name] for hp_name in config if config[hp_name] is not None }
def test_uniformfloat_transform(self): """This checks whether a value sampled through the configuration space (it does not happend when the variable is sampled alone) stays equal when it is serialized via JSON and the deserialized again.""" cs = ConfigurationSpace() a = cs.add_hyperparameter(UniformFloatHyperparameter('a', -5, 10)) b = cs.add_hyperparameter( NormalFloatHyperparameter('b', 1, 2, log=True)) for i in range(100): config = cs.sample_configuration() value = OrderedDict(sorted(config.get_dictionary().items())) string = json.dumps(value) saved_value = json.loads(string) saved_value = OrderedDict(sorted(byteify(saved_value).items())) self.assertEqual(repr(value), repr(saved_value)) # Next, test whether the truncation also works when initializing the # Configuration with a dictionary for i in range(100): rs = np.random.RandomState(1) value_a = a.sample(rs) value_b = b.sample(rs) values_dict = {'a': value_a, 'b': value_b} config = Configuration(cs, values=values_dict) string = json.dumps(config.get_dictionary()) saved_value = json.loads(string) saved_value = byteify(saved_value) self.assertEqual(values_dict, saved_value)
def _test_random_neigbor(self, hp): cs = ConfigurationSpace() if not isinstance(hp, list): hp = [hp] for hp_ in hp: cs.add_hyperparameter(hp_) cs.seed(1) config = cs.sample_configuration() for i in range(100): new_config = get_random_neighbor(config, i) self.assertNotEqual(config, new_config)
def test_sample_configuration(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("parent", [0, 1]) cs.add_hyperparameter(hp1) hp2 = UniformIntegerHyperparameter("child", 0, 10) cs.add_hyperparameter(hp2) cond1 = EqualsCondition(hp2, hp1, 0) cs.add_condition(cond1) # This automatically checks the configuration! Configuration(cs, dict(parent=0, child=5)) # and now for something more complicated cs = ConfigurationSpace(seed=1) hp1 = CategoricalHyperparameter("input1", [0, 1]) cs.add_hyperparameter(hp1) hp2 = CategoricalHyperparameter("input2", [0, 1]) cs.add_hyperparameter(hp2) hp3 = CategoricalHyperparameter("input3", [0, 1]) cs.add_hyperparameter(hp3) hp4 = CategoricalHyperparameter("input4", [0, 1]) cs.add_hyperparameter(hp4) hp5 = CategoricalHyperparameter("input5", [0, 1]) cs.add_hyperparameter(hp5) hp6 = Constant("AND", "True") cs.add_hyperparameter(hp6) cond1 = EqualsCondition(hp6, hp1, 1) cond2 = NotEqualsCondition(hp6, hp2, 1) cond3 = InCondition(hp6, hp3, [1]) cond4 = EqualsCondition(hp5, hp3, 1) cond5 = EqualsCondition(hp4, hp5, 1) cond6 = EqualsCondition(hp6, hp4, 1) cond7 = EqualsCondition(hp6, hp5, 1) conj1 = AndConjunction(cond1, cond2) conj2 = OrConjunction(conj1, cond3) conj3 = AndConjunction(conj2, cond6, cond7) cs.add_condition(cond4) cs.add_condition(cond5) cs.add_condition(conj3) samples = [] for i in range(5): cs.seed(1) samples.append([]) for j in range(100): sample = cs.sample_configuration() samples[-1].append(sample) if i > 0: for j in range(100): self.assertEqual(samples[-1][j], samples[-2][j])
def test_sample_no_configuration(self): cs = ConfigurationSpace() rval = cs.sample_configuration(size=0) self.assertEqual(len(rval), 0)