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_add_hyperparameters_with_equal_names(self): cs = ConfigurationSpace() hp = UniformIntegerHyperparameter("name", 0, 10) cs.add_hyperparameter(hp) self.assertRaisesRegex(ValueError, "Hyperparameter 'name' is already in the " "configuration space.", cs.add_hyperparameter, hp)
def setUp(self): cs = ConfigurationSpace() hp1 = cs.add_hyperparameter(CategoricalHyperparameter("parent", [0, 1])) hp2 = cs.add_hyperparameter( UniformIntegerHyperparameter("child", 0, 10)) hp3 = cs.add_hyperparameter( UniformIntegerHyperparameter("friend", 0, 5)) self.cs = cs
def test_hyperparameters_with_valid_condition(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("parent", [0, 1]) cs.add_hyperparameter(hp1) hp2 = UniformIntegerHyperparameter("child", 0, 10) cs.add_hyperparameter(hp2) cond = EqualsCondition(hp2, hp1, 0) cs.add_condition(cond) self.assertEqual(len(cs._hyperparameters), 2)
def _get_configuration_space( search_space: Dict[str, BaseDistribution]) -> ConfigurationSpace: config_space = ConfigurationSpace() for name, distribution in search_space.items(): config_space.add_hyperparameter( _distribution_to_hyperparameter(name, distribution)) return config_space
def test_hyperparameters_with_valid_condition(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("parent", [0, 1]) cs.add_hyperparameter(hp1) hp2 = UniformIntegerHyperparameter("child", 0, 10) cs.add_hyperparameter(hp2) cond = EqualsCondition(hp2, hp1, 0) cs.add_condition(cond) self.assertEqual(len(cs._hyperparameters), 2)
def get_config_space(): cs = ConfigurationSpace() cs.add_hyperparameter(UniformIntegerHyperparameter(name='a', lower=0, upper=100)) cs.add_hyperparameter(UniformIntegerHyperparameter(name='b', lower=0, upper=100)) return cs
def testRandomImputation(self): rs = numpy.random.RandomState(1) for i in range(0, 150, 15): # First random imputation sanity check num_samples = max(1, i * 10) num_feat = max(1, i) num_censored = int(num_samples * 0.1) X = rs.rand(num_samples, num_feat) y = numpy.sin(X[:, 0:1]) cutoff = max(y) * 0.9 y[y > cutoff] = cutoff # We have some cen data cen_X = X[:num_censored, :] cen_y = y[:num_censored] uncen_X = X[num_censored:, :] uncen_y = y[num_censored:] cen_y /= 2 cs = ConfigurationSpace() for i in range(num_feat): cs.add_hyperparameter( UniformFloatHyperparameter(name="a_%d" % i, lower=0, upper=1, default_value=0.5)) types, bounds = get_types(cs, None) self.model = RandomForestWithInstances( configspace=cs, types=types, bounds=bounds, instance_features=None, seed=1234567980, ) imputor = rfr_imputator.RFRImputator(rng=rs, cutoff=cutoff, threshold=cutoff * 10, change_threshold=0.01, max_iter=5, model=self.model) imp_y = imputor.impute(censored_X=cen_X, censored_y=cen_y, uncensored_X=uncen_X, uncensored_y=uncen_y) if imp_y is None: continue for idx in range(cen_y.shape[0]): self.assertGreater(imp_y[idx], cen_y[idx]) self.assertTrue(numpy.isfinite(imp_y).all())
def test_multi_sample_quantized_uihp(self): # This unit test covers a problem with sampling multiple entries at a time from a # configuration space with at least one UniformIntegerHyperparameter which is quantized. cs = ConfigurationSpace() cs.add_hyperparameter( UniformIntegerHyperparameter("uihp", lower=1, upper=101, q=2, log=False) ) self.assertIsNotNone(cs.sample_configuration(size=1)) self.assertEqual(10, len(cs.sample_configuration(size=10)))
def test_check_forbidden_with_sampled_vector_configuration(self): cs = ConfigurationSpace() metric = CategoricalHyperparameter("metric", ["minkowski", "other"]) cs.add_hyperparameter(metric) forbidden = ForbiddenEqualsClause(metric, "other") cs.add_forbidden_clause(forbidden) configuration = Configuration(cs, vector=np.ones(1, dtype=float)) self.assertRaisesRegex(ValueError, "violates forbidden clause", cs._check_forbidden, configuration.get_array())
def test_get_conditions(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("parent", [0, 1]) cs.add_hyperparameter(hp1) hp2 = UniformIntegerHyperparameter("child", 0, 10) cs.add_hyperparameter(hp2) self.assertEqual([], cs.get_conditions()) cond1 = EqualsCondition(hp2, hp1, 0) cs.add_condition(cond1) self.assertEqual([cond1], cs.get_conditions())
def test_check_forbidden_with_sampled_vector_configuration(self): cs = ConfigurationSpace() metric = CategoricalHyperparameter("metric", ["minkowski", "other"]) cs.add_hyperparameter(metric) forbidden = ForbiddenEqualsClause(metric, "other") cs.add_forbidden_clause(forbidden) configuration = Configuration(cs, vector=np.ones(1, dtype=float)) self.assertRaisesRegex(ValueError, "violates forbidden clause", cs._check_forbidden, configuration.get_array())
def test_get_conditions(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("parent", [0, 1]) cs.add_hyperparameter(hp1) hp2 = UniformIntegerHyperparameter("child", 0, 10) cs.add_hyperparameter(hp2) self.assertEqual([], cs.get_conditions()) cond1 = EqualsCondition(hp2, hp1, 0) cs.add_condition(cond1) self.assertEqual([cond1], cs.get_conditions())
def test_get_hyperparameters_topological_sort_simple(self): for iteration in range(10): 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))
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 get_configspace(): """ Returns the configuration space for the network to be configured in the example. """ # BOHB does not support Ordinal -> convert to Cat cs_invalid = get_complete_configspace() cs = ConfigurationSpace() for hp in cs_invalid.get_hyperparameters(): if isinstance(hp, OrdinalHyperparameter): cs.add_hyperparameter(CategoricalHyperparameter(hp.name, choices=hp.sequence)) else: cs.add_hyperparameter(hp) return cs
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_get_hyperparameters_topological_sort_simple(self): for iteration in range(10): 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))
def test_illegal_default_configuration(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("loss", ["l1", "l2"], default='l1') hp2 = CategoricalHyperparameter("penalty", ["l1", "l2"], default='l1') cs.add_hyperparameter(hp1) cs.add_hyperparameter(hp2) forb1 = ForbiddenEqualsClause(hp1, "l1") forb2 = ForbiddenEqualsClause(hp2, "l1") forb3 = ForbiddenAndConjunction(forb1, forb2) # cs.add_forbidden_clause(forb3) self.assertRaisesRegexp(ValueError, "Given vector violates forbidden clause \(Forbidden: loss == \'l1\' && " "Forbidden: penalty == \'l1\'\)", cs.add_forbidden_clause, forb3)
def test_get_hyperparameter(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("parent", [0, 1]) cs.add_hyperparameter(hp1) hp2 = UniformIntegerHyperparameter("child", 0, 10) cs.add_hyperparameter(hp2) retval = cs.get_hyperparameter("parent") self.assertEqual(hp1, retval) retval = cs.get_hyperparameter("child") self.assertEqual(hp2, retval) self.assertRaises(KeyError, cs.get_hyperparameter, "grandfather")
def test_illegal_default_configuration(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("loss", ["l1", "l2"], default_value='l1') hp2 = CategoricalHyperparameter("penalty", ["l1", "l2"], default_value='l1') cs.add_hyperparameter(hp1) cs.add_hyperparameter(hp2) forb1 = ForbiddenEqualsClause(hp1, "l1") forb2 = ForbiddenEqualsClause(hp2, "l1") forb3 = ForbiddenAndConjunction(forb1, forb2) # cs.add_forbidden_clause(forb3) self.assertRaisesRegexp(ValueError, "Given vector violates forbidden clause \(Forbidden: loss == \'l1\' && " "Forbidden: penalty == \'l1\'\)", cs.add_forbidden_clause, forb3)
def test_condition_with_cycles(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) cond2 = EqualsCondition(hp1, hp2, 0) self.assertRaisesRegex(ValueError, r"Hyperparameter configuration " r"contains a cycle \[\['child', 'parent'\]\]", cs.add_condition, cond2)
def test_condition_with_cycles(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) cond2 = EqualsCondition(hp1, hp2, 0) self.assertRaisesRegex(ValueError, r"Hyperparameter configuration " r"contains a cycle \[\['child', 'parent'\]\]", cs.add_condition, cond2)
def test_get_hyperparameter(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("parent", [0, 1]) cs.add_hyperparameter(hp1) hp2 = UniformIntegerHyperparameter("child", 0, 10) cs.add_hyperparameter(hp2) retval = cs.get_hyperparameter("parent") self.assertEqual(hp1, retval) retval = cs.get_hyperparameter("child") self.assertEqual(hp2, retval) self.assertRaises(KeyError, cs.get_hyperparameter, "grandfather")
def test_setitem(self): ''' Checks overriding a sampled configuration ''' pcs = ConfigurationSpace() pcs.add_hyperparameter(UniformIntegerHyperparameter('x0', 1, 5, default_value=1)) x1 = pcs.add_hyperparameter(CategoricalHyperparameter('x1', ['ab', 'bc', 'cd', 'de'], default_value='ab')) # Condition x2 = pcs.add_hyperparameter(CategoricalHyperparameter('x2', [1, 2])) pcs.add_condition(EqualsCondition(x2, x1, 'ab')) # Forbidden x3 = pcs.add_hyperparameter(CategoricalHyperparameter('x3', [1, 2])) pcs.add_forbidden_clause(ForbiddenEqualsClause(x3, 2)) conf = pcs.get_default_configuration() # failed because it's a invalid configuration with self.assertRaisesRegex(ValueError, "Illegal value '0' for hyperparameter x0"): conf['x0'] = 0 # failed because the variable didn't exists with self.assertRaisesRegex(KeyError, "Hyperparameter 'x_0' does not exist in this configuration space."): conf['x_0'] = 1 # failed because forbidden clause is violated with self.assertRaisesRegex(ForbiddenValueError, "Given vector violates forbidden clause Forbidden: x3 == 2"): conf['x3'] = 2 self.assertEqual(conf['x3'], 1) # successful operation 1 x0_old = conf['x0'] if x0_old == 1: conf['x0'] = 2 else: conf['x0'] = 1 x0_new = conf['x0'] self.assertNotEqual(x0_old, x0_new) pcs._check_configuration_rigorous(conf) self.assertEqual(conf['x2'], 1) # successful operation 2 x1_old = conf['x1'] if x1_old == 'ab': conf['x1'] = 'cd' else: conf['x1'] = 'ab' x1_new = conf['x1'] self.assertNotEqual(x1_old, x1_new) pcs._check_configuration_rigorous(conf) self.assertRaises(KeyError, conf.__getitem__, 'x2')
def test_get_hyperparameters_topological_sort(self): # and now for something more complicated cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("input1", [0, 1]) hp2 = CategoricalHyperparameter("input2", [0, 1]) hp3 = CategoricalHyperparameter("input3", [0, 1]) hp4 = CategoricalHyperparameter("input4", [0, 1]) hp5 = CategoricalHyperparameter("input5", [0, 1]) hp6 = Constant("AND", "True") # More top-level hyperparameters hp7 = CategoricalHyperparameter("input7", [0, 1]) # Somewhat shuffled hyperparameters = [hp1, hp2, hp3, hp4, hp5, hp6, hp7] for hp in hyperparameters: cs.add_hyperparameter(hp) 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) hps = cs.get_hyperparameters() # AND is moved to the front because of alphabetical sorting for hp, idx in zip(hyperparameters, [1, 2, 3, 4, 6, 0, 5]): self.assertEqual(hps.index(hp), idx) self.assertEqual(cs._hyperparameter_idx[hp.name], idx) self.assertEqual(cs._idx_to_hyperparameter[idx], hp.name) cs.add_condition(cond5) hps = cs.get_hyperparameters() for hp, idx in zip(hyperparameters, [1, 2, 3, 6, 5, 0, 4]): self.assertEqual(hps.index(hp), idx) self.assertEqual(cs._hyperparameter_idx[hp.name], idx) self.assertEqual(cs._idx_to_hyperparameter[idx], hp.name) cs.add_condition(conj3) hps = cs.get_hyperparameters() # print(hps, hyperparameters) for hp, idx in zip(hyperparameters, [0, 1, 2, 5, 4, 6, 3]): # print(hp, idx) self.assertEqual(hps.index(hp), idx) self.assertEqual(cs._hyperparameter_idx[hp.name], idx) self.assertEqual(cs._idx_to_hyperparameter[idx], hp.name)
def test_setitem(self): ''' Checks overriding a sampled configuration ''' pcs = ConfigurationSpace() pcs.add_hyperparameter(UniformIntegerHyperparameter('x0', 1, 5, default_value=1)) x1 = pcs.add_hyperparameter(CategoricalHyperparameter('x1', ['ab', 'bc', 'cd', 'de'], default_value='ab')) # Condition x2 = pcs.add_hyperparameter(CategoricalHyperparameter('x2', [1, 2])) pcs.add_condition(EqualsCondition(x2, x1, 'ab')) # Forbidden x3 = pcs.add_hyperparameter(CategoricalHyperparameter('x3', [1, 2])) pcs.add_forbidden_clause(ForbiddenEqualsClause(x3, 2)) conf = pcs.get_default_configuration() # failed because it's a invalid configuration with self.assertRaisesRegex(ValueError, "Illegal value '0' for hyperparameter x0"): conf['x0'] = 0 # failed because the variable didn't exists with self.assertRaisesRegex(KeyError, "Hyperparameter 'x_0' does not exist in this configuration space."): conf['x_0'] = 1 # failed because forbidden clause is violated with self.assertRaisesRegex(ForbiddenValueError, "Given vector violates forbidden clause Forbidden: x3 == 2"): conf['x3'] = 2 self.assertEqual(conf['x3'], 1) # successful operation 1 x0_old = conf['x0'] if x0_old == 1: conf['x0'] = 2 else: conf['x0'] = 1 x0_new = conf['x0'] self.assertNotEqual(x0_old, x0_new) pcs._check_configuration_rigorous(conf) self.assertEqual(conf['x2'], 1) # successful operation 2 x1_old = conf['x1'] if x1_old == 'ab': conf['x1'] = 'cd' else: conf['x1'] = 'ab' x1_new = conf['x1'] self.assertNotEqual(x1_old, x1_new) pcs._check_configuration_rigorous(conf) self.assertRaises(KeyError, conf.__getitem__, 'x2')
def test_get_hyperparameters_topological_sort(self): # and now for something more complicated cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("input1", [0, 1]) hp2 = CategoricalHyperparameter("input2", [0, 1]) hp3 = CategoricalHyperparameter("input3", [0, 1]) hp4 = CategoricalHyperparameter("input4", [0, 1]) hp5 = CategoricalHyperparameter("input5", [0, 1]) hp6 = Constant("AND", "True") # More top-level hyperparameters hp7 = CategoricalHyperparameter("input7", [0, 1]) # Somewhat shuffled hyperparameters = [hp1, hp2, hp3, hp4, hp5, hp6, hp7] for hp in hyperparameters: cs.add_hyperparameter(hp) 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) hps = cs.get_hyperparameters() # AND is moved to the front because of alphabetical sorting for hp, idx in zip(hyperparameters, [1, 2, 3, 4, 6, 0, 5]): self.assertEqual(hps.index(hp), idx) self.assertEqual(cs._hyperparameter_idx[hp.name], idx) self.assertEqual(cs._idx_to_hyperparameter[idx], hp.name) cs.add_condition(cond5) hps = cs.get_hyperparameters() for hp, idx in zip(hyperparameters, [1, 2, 3, 6, 5, 0, 4]): self.assertEqual(hps.index(hp), idx) self.assertEqual(cs._hyperparameter_idx[hp.name], idx) self.assertEqual(cs._idx_to_hyperparameter[idx], hp.name) cs.add_condition(conj3) hps = cs.get_hyperparameters() # print(hps, hyperparameters) for hp, idx in zip(hyperparameters, [0, 1, 2, 5, 4, 6, 3]): # print(hp, idx) self.assertEqual(hps.index(hp), idx) self.assertEqual(cs._hyperparameter_idx[hp.name], idx) self.assertEqual(cs._idx_to_hyperparameter[idx], hp.name)
def test_merge_foreign_data(self): ''' test smac.utils.merge_foreign_data ''' scenario = Scenario(self.test_scenario_dict) scenario_2 = Scenario(self.test_scenario_dict) scenario_2.feature_dict = {"inst_new": [4]} # init cs cs = ConfigurationSpace() cs.add_hyperparameter(UniformIntegerHyperparameter(name='a', lower=0, upper=100)) cs.add_hyperparameter(UniformIntegerHyperparameter(name='b', lower=0, upper=100)) # build runhistory rh_merge = RunHistory(aggregate_func=average_cost) config = Configuration(cs, values={'a': 1, 'b': 2}) rh_merge.add(config=config, instance_id="inst_new", cost=10, time=20, status=StatusType.SUCCESS, seed=None, additional_info=None) # "d" is an instance in <scenario> rh_merge.add(config=config, instance_id="d", cost=5, time=20, status=StatusType.SUCCESS, seed=None, additional_info=None) # build empty rh rh_base = RunHistory(aggregate_func=average_cost) merge_foreign_data(scenario=scenario, runhistory=rh_base, in_scenario_list=[scenario_2], in_runhistory_list=[rh_merge]) # both runs should be in the runhistory # but we should not use the data to update the cost of config self.assertTrue(len(rh_base.data) == 2) self.assertTrue(np.isnan(rh_base.get_cost(config))) # we should not get direct access to external run data runs = rh_base.get_runs_for_config(config) self.assertTrue(len(runs) == 0) rh_merge.add(config=config, instance_id="inst_new_2", cost=10, time=20, status=StatusType.SUCCESS, seed=None, additional_info=None) self.assertRaises(ValueError, merge_foreign_data, **{ "scenario": scenario, "runhistory": rh_base, "in_scenario_list": [scenario_2], "in_runhistory_list": [rh_merge]})
def test_get_hyperparamforbidden_clauseseters(self): cs = ConfigurationSpace() self.assertEqual(0, len(cs.get_hyperparameters())) hp1 = CategoricalHyperparameter("parent", [0, 1]) cs.add_hyperparameter(hp1) self.assertEqual([hp1], cs.get_hyperparameters()) hp2 = UniformIntegerHyperparameter("child", 0, 10) cs.add_hyperparameter(hp2) cond1 = EqualsCondition(hp2, hp1, 1) cs.add_condition(cond1) self.assertEqual([hp1, hp2], cs.get_hyperparameters()) # TODO: I need more tests for the topological sort! self.assertEqual([hp1, hp2], cs.get_hyperparameters())
def test_get_hyperparamforbidden_clauseseters(self): cs = ConfigurationSpace() self.assertEqual(0, len(cs.get_hyperparameters())) hp1 = CategoricalHyperparameter("parent", [0, 1]) cs.add_hyperparameter(hp1) self.assertEqual([hp1], cs.get_hyperparameters()) hp2 = UniformIntegerHyperparameter("child", 0, 10) cs.add_hyperparameter(hp2) cond1 = EqualsCondition(hp2, hp1, 1) cs.add_condition(cond1) self.assertEqual([hp1, hp2], cs.get_hyperparameters()) # TODO: I need more tests for the topological sort! self.assertEqual([hp1, hp2], cs.get_hyperparameters())
def sacred_space_to_configspace(space): """ Convert a Labwatch searchspace to a ConfigSpace. Parameters ---------- space: labwatch.searchspace.SearchSpace A labwatch searchspace to be converted. Returns ------- ConfigSpace.ConfigurationSpace: A ConfigurationSpace equivalent to the given SeachSpace. """ # first convert all non conditionals non_conditions = {} conditions = [] for name in space.non_conditions: param = space.parameters[name] converted_param = convert_simple_param(name, param) non_conditions[name] = converted_param for name in space.conditions: param = space.parameters[name] converted_result = convert_simple_param(name, param["result"]) # next build the condition as required by the ConfigSpace condition = param["condition"] condition_name = space.uids_to_names[condition["uid"]] if condition_name not in non_conditions: raise ValueError("Unknown parameter in Condition") converted_condition = non_conditions[condition_name] converted_choices = [] for choice in condition["choices"]: if isinstance(choice, dict): if choice["_class"] != "Constant": raise ValueError("Invalid choice encountered in Condition") converted_choices.append(choice["value"]) else: converted_choices.append(choice) cond = InCondition(converted_result, converted_condition, values=converted_choices) non_conditions[name] = converted_result conditions.append(cond) # finally build the ConfigSpace cs = ConfigurationSpace(seed=np.random.seed()) for _name, param in non_conditions.items(): cs.add_hyperparameter(param) for cond in conditions: cs.add_condition(cond) return cs
def test_add_forbidden_clause(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("input1", [0, 1]) cs.add_hyperparameter(hp1) forb = ForbiddenEqualsClause(hp1, 1) # TODO add checking whether a forbidden clause makes sense at all cs.add_forbidden_clause(forb) # TODO add something to properly retrieve the forbidden clauses self.assertEqual(str(cs), "Configuration space object:\n " "Hyperparameters:\n input1, " "Type: Categorical, Choices: {0, 1}, " "Default: 0\n" " Forbidden Clauses:\n" " Forbidden: input1 == 1\n")
def test_add_forbidden_clause(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("input1", [0, 1]) cs.add_hyperparameter(hp1) forb = ForbiddenEqualsClause(hp1, 1) # TODO add checking whether a forbidden clause makes sense at all cs.add_forbidden_clause(forb) # TODO add something to properly retrieve the forbidden clauses self.assertEqual(str(cs), "Configuration space object:\n " "Hyperparameters:\n input1, " "Type: Categorical, Choices: {0, 1}, " "Default: 0\n" " Forbidden Clauses:\n" " Forbidden: input1 == 1\n")
def get_cash_cs(include_algorithms=None, task_type=CLASSIFICATION): _candidates = get_combined_candidtates(_classifiers, _addons) if include_algorithms is not None: _candidates = set(include_algorithms).intersection(set(_candidates.keys())) if len(_candidates) == 0: raise ValueError("No algorithms included! Please check the spelling of the included algorithms!") cs = ConfigurationSpace() algo = CategoricalHyperparameter('algorithm', list(_candidates)) cs.add_hyperparameter(algo) for estimator_id in _candidates: estimator_cs = get_hpo_cs(estimator_id) parent_hyperparameter = {'parent': algo, 'value': estimator_id} cs.add_configuration_space(estimator_id, estimator_cs, parent_hyperparameter=parent_hyperparameter) return cs
def create_cs_from_pandaframe(self, data): # TODO use from pyimp after https://github.com/automl/ParameterImportance/issues/72 is implemented warnings.warn( "No parameter configuration space (pcs) provided! " "Interpreting all parameters as floats. This might lead " "to suboptimal analysis.", RuntimeWarning) self.logger.debug("Interpreting as parameters: %s", data.columns) minima = data.min() # to define ranges of hyperparameter maxima = data.max() cs = ConfigurationSpace(seed=42) for p in data.columns: cs.add_hyperparameter( UniformFloatHyperparameter(p, lower=minima[p] - 1, upper=maxima[p] + 1))
def test_get_one_exchange_neighbourhood(self): # test fixed_dims cs = ConfigurationSpace() cs.add_hyperparameter( CategoricalHyperparameter('0', [0, 1], default_value=0)) cs.add_hyperparameter( CategoricalHyperparameter('1', [0, 1], default_value=0)) cs.add_hyperparameter( CategoricalHyperparameter('2', [0, 1], default_value=0)) cs.add_hyperparameter( CategoricalHyperparameter('3', [0, 1], default_value=0)) cs.add_hyperparameter( CategoricalHyperparameter('4', [0, 1, 2, 3, 4], default_value=0)) fixed_dims = {'0': 1, '1': 0, '2': 0, '3': 0} conf = cs.sample_configuration(fixed_dims=fixed_dims) neighborhood_iter = get_one_exchange_neighbourhood( conf, seed=0, fixed_dims=fixed_dims) tmp = next(neighborhood_iter) self.assertEqual(tmp['0'], fixed_dims['0']) self.assertEqual(tmp['1'], fixed_dims['1']) self.assertEqual(tmp['2'], fixed_dims['2']) self.assertEqual(tmp['3'], fixed_dims['3']) tmp = next(neighborhood_iter) self.assertEqual(tmp['0'], fixed_dims['0']) self.assertEqual(tmp['1'], fixed_dims['1']) self.assertEqual(tmp['2'], fixed_dims['2']) self.assertEqual(tmp['3'], fixed_dims['3']) tmp = next(neighborhood_iter) self.assertEqual(tmp['0'], fixed_dims['0']) self.assertEqual(tmp['1'], fixed_dims['1']) self.assertEqual(tmp['2'], fixed_dims['2']) self.assertEqual(tmp['3'], fixed_dims['3']) tmp = next(neighborhood_iter) self.assertEqual(tmp['0'], fixed_dims['0']) self.assertEqual(tmp['1'], fixed_dims['1']) self.assertEqual(tmp['2'], fixed_dims['2']) self.assertEqual(tmp['3'], fixed_dims['3']) # StopIteration with self.assertRaises(StopIteration): tmp = next(neighborhood_iter)
def test_add_configuration_space(self): cs = ConfigurationSpace() hp1 = cs.add_hyperparameter(CategoricalHyperparameter("input1", [0, 1])) cs.add_forbidden_clause(ForbiddenEqualsClause(hp1, 1)) hp2 = cs.add_hyperparameter(UniformIntegerHyperparameter("child", 0, 10)) cs.add_condition(EqualsCondition(hp2, hp1, 0)) cs2 = ConfigurationSpace() cs2.add_configuration_space('prefix', cs, delimiter='__') self.assertEqual(str(cs2), '''Configuration space object: Hyperparameters: prefix__child, Type: UniformInteger, Range: [0, 10], Default: 5 prefix__input1, Type: Categorical, Choices: {0, 1}, Default: 0 Conditions: prefix__child | prefix__input1 == 0 Forbidden Clauses: Forbidden: prefix__input1 == 1 ''')
def test_add_configuration_space(self): cs = ConfigurationSpace() hp1 = cs.add_hyperparameter(CategoricalHyperparameter("input1", [0, 1])) cs.add_forbidden_clause(ForbiddenEqualsClause(hp1, 1)) hp2 = cs.add_hyperparameter(UniformIntegerHyperparameter("child", 0, 10)) cs.add_condition(EqualsCondition(hp2, hp1, 0)) cs2 = ConfigurationSpace() cs2.add_configuration_space('prefix', cs, delimiter='__') self.assertEqual(str(cs2), '''Configuration space object: Hyperparameters: prefix__child, Type: UniformInteger, Range: [0, 10], Default: 5 prefix__input1, Type: Categorical, Choices: {0, 1}, Default: 0 Conditions: prefix__child | prefix__input1 == 0 Forbidden Clauses: Forbidden: prefix__input1 == 1 ''')
def test_estimate_size(self): cs = ConfigurationSpace() self.assertEqual(cs.estimate_size(), 0) cs.add_hyperparameter(Constant('constant', 0)) self.assertEqual(cs.estimate_size(), 1) cs.add_hyperparameter(UniformIntegerHyperparameter('integer', 0, 5)) self.assertEqual(cs.estimate_size(), 6) cs.add_hyperparameter(CategoricalHyperparameter('cat', [0, 1, 2])) self.assertEqual(cs.estimate_size(), 18) cs.add_hyperparameter(UniformFloatHyperparameter('float', 0, 1)) self.assertTrue(np.isinf(cs.estimate_size()))
class TestLHDesign(unittest.TestCase): def setUp(self): def get_uniform_param(name: str): return UniformFloatHyperparameter(name, 0, 1) def get_constant_param(name: str): return Constant(name, 0.) def get_categorical_param(name: str): return CategoricalHyperparameter(name, choices=["a", "b", "c"]) def get_ordinal_param(name: str): return OrdinalHyperparameter(name, [8, 6, 4, 2]) get_params = [ get_uniform_param, get_constant_param, get_categorical_param, get_ordinal_param ] self.cs = ConfigurationSpace() for j, get_param in enumerate(get_params): param_name = f"x{j}" self.cs.add_hyperparameter(get_param(param_name)) for i in range(5): self.cs.add_hyperparameter(UniformFloatHyperparameter('x%d' % (i + len(get_params)), 0, 1)) def test_latin_hypercube_design(self): kwargs = dict( rng=np.random.RandomState(1), traj_logger=unittest.mock.Mock(), ta_run_limit=1000, configs=None, n_configs_x_params=None, max_config_fracs=0.25, init_budget=1, ) LHDesign( cs=self.cs, **kwargs ).select_configurations()
def test_condition_without_added_hyperparameters(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("parent", [0, 1]) hp2 = UniformIntegerHyperparameter("child", 0, 10) cond = EqualsCondition(hp2, hp1, 0) self.assertRaisesRegex(ValueError, "Child hyperparameter 'child' not " "in configuration space.", cs.add_condition, cond) cs.add_hyperparameter(hp1) self.assertRaisesRegex(ValueError, "Child hyperparameter 'child' not " "in configuration space.", cs.add_condition, cond) # Test also the parent hyperparameter cs2 = ConfigurationSpace() cs2.add_hyperparameter(hp2) self.assertRaisesRegex(ValueError, "Parent hyperparameter 'parent' " "not in configuration space.", cs2.add_condition, cond)
def evaluate(_config): _config = _config.get_dictionary() # print(_config) arm = None cs = ConfigurationSpace() for key in _config: key_str = key.split(":") if key_str[0] == 'classifier': if key_str[1] == '__choice__': arm = _config[key] cs.add_hyperparameter( UnParametrizedHyperparameter("estimator", _config[key])) else: cs.add_hyperparameter( UnParametrizedHyperparameter(key_str[2], _config[key])) if arm in first_bandit.arms: transformed_node = apply_metalearning_fe( first_bandit.sub_bandits[arm].optimizer['fe'], _config) default_config = cs.sample_configuration(1) hpo_evaluator = ClassificationEvaluator( None, data_node=transformed_node, name='hpo', resampling_strategy=first_bandit.eval_type, seed=first_bandit.seed) start_time = time.time() score1 = -hpo_evaluator(default_config) time_cost1 = time.time() - start_time # Evaluate the default config start_time = time.time() score2 = -hpo_evaluator( first_bandit.sub_bandits[arm].default_config) time_cost2 = time.time() - start_time transformed_node.score2 = max(score1, score2) return (arm, score1, default_config, transformed_node, time_cost1), (arm, score2, first_bandit.sub_bandits[arm].default_config, transformed_node, time_cost2)
def test_add_second_condition_wo_conjunction(self): hp1 = CategoricalHyperparameter("input1", [0, 1]) hp2 = CategoricalHyperparameter("input2", [0, 1]) hp3 = Constant("And", "True") cond1 = EqualsCondition(hp3, hp1, 1) cond2 = EqualsCondition(hp3, hp2, 1) cs = ConfigurationSpace() cs.add_hyperparameter(hp1) cs.add_hyperparameter(hp2) cs.add_hyperparameter(hp3) cs.add_condition(cond1) self.assertRaisesRegex( ValueError, r"Adding a second condition \(different\) for a " r"hyperparameter is ambigouos and " r"therefore forbidden. Add a conjunction " r"instead!", cs.add_condition, cond2)
def get_configspace(self, optimizer='smac'): if optimizer == 'smac': cs = ConfigurationSpace() for i in range(self.dim): xi = UniformFloatHyperparameter("x%d" % i, self.lb, self.ub) cs.add_hyperparameter(xi) return cs elif optimizer == 'tpe': from hyperopt import hp space = {'x%d' % i: hp.uniform('hp_x%d' % i, self.lb, self.ub) for i in range(self.dim)} return space elif optimizer == 'gpflowopt': import gpflowopt domain = np.sum([ gpflowopt.domain.ContinuousParameter('x%d' % i, self.lb, self.ub) for i in range(self.dim) ]) return domain else: raise ValueError('Unknown optimizer %s when getting configspace' % optimizer)
def test_condition_without_added_hyperparameters(self): cs = ConfigurationSpace() hp1 = CategoricalHyperparameter("parent", [0, 1]) hp2 = UniformIntegerHyperparameter("child", 0, 10) cond = EqualsCondition(hp2, hp1, 0) self.assertRaisesRegex( ValueError, "Child hyperparameter 'child' not " "in configuration space.", cs.add_condition, cond) cs.add_hyperparameter(hp1) self.assertRaisesRegex( ValueError, "Child hyperparameter 'child' not " "in configuration space.", cs.add_condition, cond) # Test also the parent hyperparameter cs2 = ConfigurationSpace() cs2.add_hyperparameter(hp2) self.assertRaisesRegex( ValueError, "Parent hyperparameter 'parent' " "not in configuration space.", cs2.add_condition, cond)
def test_choose_next(self): configspace = ConfigurationSpace() configspace.add_hyperparameter(UniformFloatHyperparameter('a', 0, 1)) configspace.add_hyperparameter(UniformFloatHyperparameter('b', 0, 1)) dataset_name = 'foo' func_eval_time_limit = 15 total_walltime_limit = 15 memory_limit = 3072 auto = AutoMLSMBO(config_space=None, dataset_name=dataset_name, backend=None, func_eval_time_limit=func_eval_time_limit, total_walltime_limit=total_walltime_limit, memory_limit=memory_limit, watcher=None, metric=accuracy) auto.config_space = configspace scenario = Scenario({ 'cs': configspace, 'cutoff-time': func_eval_time_limit, 'wallclock-limit': total_walltime_limit, 'memory-limit': memory_limit, 'run-obj': 'quality' }) smac = SMAC(scenario) self.assertRaisesRegex( ValueError, 'Cannot use SMBO algorithm on ' 'empty runhistory', auto.choose_next, smac) config = Configuration(configspace, values={'a': 0.1, 'b': 0.2}) # TODO make sure the incumbent is always set? smac.solver.incumbent = config runhistory = smac.solver.runhistory runhistory.add(config=config, cost=0.5, time=0.5, status=StatusType.SUCCESS) auto.choose_next(smac)
def test_add_second_condition_wo_conjunction(self): hp1 = CategoricalHyperparameter("input1", [0, 1]) hp2 = CategoricalHyperparameter("input2", [0, 1]) hp3 = Constant("And", "True") cond1 = EqualsCondition(hp3, hp1, 1) cond2 = EqualsCondition(hp3, hp2, 1) cs = ConfigurationSpace() cs.add_hyperparameter(hp1) cs.add_hyperparameter(hp2) cs.add_hyperparameter(hp3) cs.add_condition(cond1) self.assertRaisesRegex(ValueError, r"Adding a second condition \(different\) for a " r"hyperparameter is ambigouos and " r"therefore forbidden. Add a conjunction " r"instead!", cs.add_condition, cond2)
def test_add_conjunction(self): hp1 = CategoricalHyperparameter("input1", [0, 1]) hp2 = CategoricalHyperparameter("input2", [0, 1]) hp3 = CategoricalHyperparameter("input3", [0, 1]) hp4 = Constant("And", "True") cond1 = EqualsCondition(hp4, hp1, 1) cond2 = EqualsCondition(hp4, hp2, 1) cond3 = EqualsCondition(hp4, hp3, 1) andconj1 = AndConjunction(cond1, cond2, cond3) cs = ConfigurationSpace() cs.add_hyperparameter(hp1) cs.add_hyperparameter(hp2) cs.add_hyperparameter(hp3) cs.add_hyperparameter(hp4) cs.add_condition(andconj1) self.assertNotIn(hp4, cs.get_all_unconditional_hyperparameters())
def test_repr(self): cs1 = ConfigurationSpace() retval = cs1.__str__() self.assertEqual("Configuration space object:\n Hyperparameters:\n", retval) hp1 = CategoricalHyperparameter("parent", [0, 1]) cs1.add_hyperparameter(hp1) retval = cs1.__str__() self.assertEqual("Configuration space object:\n Hyperparameters:\n" " %s\n" % str(hp1), retval) hp2 = UniformIntegerHyperparameter("child", 0, 10) cond1 = EqualsCondition(hp2, hp1, 0) cs1.add_hyperparameter(hp2) cs1.add_condition(cond1) retval = cs1.__str__() self.assertEqual("Configuration space object:\n Hyperparameters:\n" " %s\n %s\n Conditions:\n %s\n" % (str(hp2), str(hp1), str(cond1)), retval)
def test_add_configuration_space_conjunctions(self): cs1 = ConfigurationSpace() cs2 = ConfigurationSpace() hp1 = cs1.add_hyperparameter(CategoricalHyperparameter("input1", [0, 1])) hp2 = cs1.add_hyperparameter(CategoricalHyperparameter("input2", [0, 1])) hp3 = cs1.add_hyperparameter(UniformIntegerHyperparameter("child1", 0, 10)) hp4 = cs1.add_hyperparameter(UniformIntegerHyperparameter("child2", 0, 10)) cond1 = EqualsCondition(hp2, hp3, 0) cond2 = EqualsCondition(hp1, hp3, 5) cond3 = EqualsCondition(hp1, hp4, 1) andCond = AndConjunction(cond2, cond3) cs1.add_conditions([cond1, andCond]) cs2.add_configuration_space(prefix='test', configuration_space=cs1) self.assertEqual(str(cs2).count('test:'), 10) # Check that they're equal except for the "test:" prefix self.assertEqual(str(cs1), str(cs2).replace('test:', ''))
def test_check_configuration2(self): # Test that hyperparameters which are not active must not be set and # that evaluating forbidden clauses does not choke on missing # hyperparameters cs = ConfigurationSpace() classifier = CategoricalHyperparameter("classifier", ["k_nearest_neighbors", "extra_trees"]) metric = CategoricalHyperparameter("metric", ["minkowski", "other"]) p = CategoricalHyperparameter("k_nearest_neighbors:p", [1, 2]) metric_depends_on_classifier = EqualsCondition(metric, classifier, "k_nearest_neighbors") p_depends_on_metric = EqualsCondition(p, metric, "minkowski") cs.add_hyperparameter(metric) cs.add_hyperparameter(p) cs.add_hyperparameter(classifier) cs.add_condition(metric_depends_on_classifier) cs.add_condition(p_depends_on_metric) forbidden = ForbiddenEqualsClause(metric, "other") cs.add_forbidden_clause(forbidden) configuration = Configuration(cs, dict(classifier="extra_trees")) # check backward compatibility with checking configurations instead of vectors cs.check_configuration(configuration)
def _test_get_one_exchange_neighbourhood(self, hp): cs = ConfigurationSpace() num_neighbors = 0 if not isinstance(hp, list): hp = [hp] for hp_ in hp: cs.add_hyperparameter(hp_) if np.isinf(hp_.get_num_neighbors()): num_neighbors += 4 else: num_neighbors += hp_.get_num_neighbors() cs.seed(1) config = cs.get_default_configuration() all_neighbors = [] for i in range(100): neighborhood = get_one_exchange_neighbourhood(config, i) for new_config in neighborhood: self.assertNotEqual(config, new_config) all_neighbors.append(new_config) return all_neighbors
def test_get_parent_and_children_of(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) self.assertEqual([hp1], cs.get_parents_of(hp2.name)) self.assertEqual([hp1], cs.get_parents_of(hp2)) self.assertEqual([hp2], cs.get_children_of(hp1.name)) self.assertEqual([hp2], cs.get_children_of(hp1)) self.assertRaisesRegex(KeyError, "Hyperparameter 'Foo' does not exist in this " "configuration space.", cs.get_parents_of, "Foo") self.assertRaisesRegex(KeyError, "Hyperparameter 'Foo' does not exist in this " "configuration space.", cs.get_children_of, "Foo")
def test_eq(self): # Compare empty configuration spaces cs1 = ConfigurationSpace() cs2 = ConfigurationSpace() self.assertEqual(cs1, cs2) # Compare to something which isn't a configuration space self.assertTrue(not (cs1 == "ConfigurationSpace")) # Compare to equal configuration spaces hp1 = CategoricalHyperparameter("parent", [0, 1]) hp2 = UniformIntegerHyperparameter("child", 0, 10) hp3 = UniformIntegerHyperparameter("friend", 0, 5) cond1 = EqualsCondition(hp2, hp1, 0) cs1.add_hyperparameter(hp1) cs1.add_hyperparameter(hp2) cs1.add_condition(cond1) cs2.add_hyperparameter(hp1) cs2.add_hyperparameter(hp2) cs2.add_condition(cond1) self.assertEqual(cs1, cs2) cs1.add_hyperparameter(hp3) self.assertFalse(cs1 == cs2)
def test_setting_illegal_value(self): cs = ConfigurationSpace() cs.add_hyperparameter(UniformFloatHyperparameter('x', 0, 1)) configuration = {'x': 2} self.assertRaises(ValueError, Configuration, cs, configuration)
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_add_hyperparameter(self): cs = ConfigurationSpace() hp = UniformIntegerHyperparameter("name", 0, 10) cs.add_hyperparameter(hp)
def test_check_configuration(self): # TODO this is only a smoke test # TODO actually, this rather tests the evaluate methods in the # conditions module! 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() 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(hp6, hp4, 1) cond5 = EqualsCondition(hp6, hp5, 1) conj1 = AndConjunction(cond1, cond2) conj2 = OrConjunction(conj1, cond3) conj3 = AndConjunction(conj2, cond4, cond5) cs.add_condition(conj3) expected_outcomes = [False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, True, False, False, False, True, False, False, False, True, False, False, False, False, False, False, False, True] for idx, values in enumerate(product([0, 1], repeat=5)): # The hyperparameters aren't sorted, but the test assumes them to # be sorted. hyperparameters = sorted(cs.get_hyperparameters(), key=lambda t: t.name) instantiations = {hyperparameters[jdx+1].name: values[jdx] for jdx in range(len(values))} evaluation = conj3.evaluate(instantiations) self.assertEqual(expected_outcomes[idx], evaluation) if not evaluation: self.assertRaisesRegex(ValueError, r"Inactive hyperparameter 'AND' must " r"not be specified, but has the vector value: " r"'0.0'.", Configuration, cs, values={ "input1": values[0], "input2": values[1], "input3": values[2], "input4": values[3], "input5": values[4], "AND": "True"}) else: Configuration(cs, values={"input1": values[0], "input2": values[1], "input3": values[2], "input4": values[3], "input5": values[4], "AND": "True"})
def test_add_conditions(self): cs1 = ConfigurationSpace() cs2 = ConfigurationSpace() hp1 = cs1.add_hyperparameter(CategoricalHyperparameter("input1", [0, 1])) cs2.add_hyperparameter(hp1) hp2 = cs1.add_hyperparameter(CategoricalHyperparameter("input2", [0, 1])) cs2.add_hyperparameter(hp2) hp3 = cs1.add_hyperparameter(UniformIntegerHyperparameter("child1", 0, 10)) cs2.add_hyperparameter(hp3) hp4 = cs1.add_hyperparameter(UniformIntegerHyperparameter("child2", 0, 10)) cs2.add_hyperparameter(hp4) cond1 = EqualsCondition(hp2, hp3, 0) cond2 = EqualsCondition(hp1, hp3, 5) cond3 = EqualsCondition(hp1, hp4, 1) andCond = AndConjunction(cond2, cond3) cs1.add_conditions([cond1, andCond]) cs2.add_condition(cond1) cs2.add_condition(andCond) self.assertEqual(str(cs1), str(cs2))