def test_condition_from_cryptominisat(self):
parent = CategoricalHyperparameter('blkrest', ['0', '1'],
default_value='1')
child = UniformIntegerHyperparameter('blkrestlen',
2000,
10000,
log=True)
condition = EqualsCondition(child, parent, '1')
self.assertFalse(condition.evaluate(dict(blkrest='0')))
self.assertTrue(condition.evaluate(dict(blkrest='1')))
def condition_specification(child_name, condition, configuration_space):
# specifies the condition type
child = configuration_space.get_hyperparameter(child_name)
parent_name = condition[0]
parent = configuration_space.get_hyperparameter(parent_name)
operation = condition[1]
if operation == 'in':
restrictions = condition[3:-1:2]
for i in range(len(restrictions)):
if isinstance(parent, FloatHyperparameter):
restrictions[i] = float(restrictions[i])
elif isinstance(parent, IntegerHyperparameter):
restrictions[i] = int(restrictions[i])
if len(restrictions) == 1:
condition = EqualsCondition(child, parent, restrictions[0])
else:
condition = InCondition(child, parent, values=restrictions)
return condition
else:
restrictions = condition[2]
if isinstance(parent, FloatHyperparameter):
restrictions = float(restrictions)
elif isinstance(parent, IntegerHyperparameter):
restrictions = int(restrictions)
if operation == '==':
condition = EqualsCondition(child, parent, restrictions)
elif operation == '!=':
condition = NotEqualsCondition(child, parent, restrictions)
else:
if isinstance(parent, FloatHyperparameter):
restrictions = float(restrictions)
elif isinstance(parent, IntegerHyperparameter):
restrictions = int(restrictions)
elif isinstance(parent, OrdinalHyperparameter):
pass
else:
raise ValueError('The parent of a conditional hyperparameter '
'must be either a float, int or ordinal '
'hyperparameter, but is %s.' % type(parent))
if operation == '<':
condition = LessThanCondition(child, parent, restrictions)
elif operation == '>':
condition = GreaterThanCondition(child, parent, restrictions)
return condition
def test_get_parents(self):
# Necessary because we couldn't call cs.get_parents for
# clasp-sat-params-nat.pcs
counter = UniformIntegerHyperparameter('bump', 10, 4096, log=True)
_1_S_countercond = CategoricalHyperparameter('cony', ['yes', 'no'])
_1_0_restarts = CategoricalHyperparameter(
'restarts', ['F', 'L', 'D', 'x', '+', 'no'], default_value='x')
condition = EqualsCondition(counter, _1_S_countercond, 'yes')
# All conditions inherit get_parents from abstractcondition
self.assertEqual([_1_S_countercond], condition.get_parents())
condition2 = InCondition(counter, _1_0_restarts,
['F', 'D', 'L', 'x', '+'])
# All conjunctions inherit get_parents from abstractconjunction
conjunction = AndConjunction(condition, condition2)
self.assertEqual([_1_S_countercond, _1_0_restarts],
conjunction.get_parents())
def _construct_eq_condition(
condition: Dict,
cs: ConfigurationSpace,
) -> EqualsCondition:
return EqualsCondition(
child=cs.get_hyperparameter(condition['child']),
parent=cs.get_hyperparameter(condition['parent']),
value=condition['value'],
)
def test_all_components_have_the_same_child(self):
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")
cond1 = EqualsCondition(hp1, hp2, 1)
cond2 = EqualsCondition(hp1, hp3, 1)
cond3 = EqualsCondition(hp1, hp4, 1)
cond4 = EqualsCondition(hp6, hp4, 1)
cond5 = EqualsCondition(hp6, hp5, 1)
AndConjunction(cond1, cond2, cond3)
AndConjunction(cond4, cond5)
self.assertRaisesRegexp(
ValueError, "All Conjunctions and Conditions must have "
"the same child.", AndConjunction, cond1, cond4)
def test_and_conjunction(self):
self.assertRaises(TypeError, AndConjunction, "String1", "String2")
hp1 = CategoricalHyperparameter("input1", [0, 1])
hp2 = CategoricalHyperparameter("input2", [0, 1])
hp3 = CategoricalHyperparameter("input3", [0, 1])
hp4 = Constant("And", "True")
cond1 = EqualsCondition(hp4, hp1, 1)
# Only one condition in an AndConjunction!
self.assertRaises(ValueError, AndConjunction, cond1)
cond2 = EqualsCondition(hp4, hp2, 1)
cond3 = EqualsCondition(hp4, hp3, 1)
andconj1 = AndConjunction(cond1, cond2)
andconj1_ = AndConjunction(cond1, cond2)
self.assertEqual(andconj1, andconj1_)
# Test setting vector idx
hyperparameter_idx = {
hp1.name: 0,
hp2.name: 1,
hp3.name: 2,
hp4.name: 3
}
andconj1.set_vector_idx(hyperparameter_idx)
self.assertEqual(andconj1.get_parents_vector(), [0, 1])
self.assertEqual(andconj1.get_children_vector(), [3, 3])
andconj2 = AndConjunction(cond2, cond3)
self.assertNotEqual(andconj1, andconj2)
andconj3 = AndConjunction(cond1, cond2, cond3)
self.assertEqual(
"(And | input1 == 1 && And | input2 == 1 && And | "
"input3 == 1)", str(andconj3))
# Test __eq__
self.assertNotEqual(andconj1, andconj3)
self.assertNotEqual(andconj1, "String")
def test_impute_inactive_hyperparameters(self):
cs = smac.configspace.ConfigurationSpace()
a = cs.add_hyperparameter(CategoricalHyperparameter('a', [0, 1],
default_value=0))
b = cs.add_hyperparameter(CategoricalHyperparameter('b', [0, 1],
default_value=1))
cs.add_condition(EqualsCondition(b, a, 1))
cs.seed(1)
configs = cs.sample_configuration(size=100)
config_array = smac.configspace.convert_configurations_to_array(configs)
for line in config_array:
if line[0] == 0:
self.assertEqual(line[1], 1)
def test_write_equals_condition_numerical(self):
expected = "temp '--temp ' i (1, 2)\nls '--ls ' c {sa,ca,ny}| temp==2\n"
temp = UniformIntegerHyperparameter("temp", 1, 2)
ls = CategoricalHyperparameter("ls", ["sa", "ca", "ny"], "sa")
cs = ConfigurationSpace()
cs.add_hyperparameter(temp)
cs.add_hyperparameter(ls)
c1 = EqualsCondition(ls, temp, 2)
cs.add_condition(c1)
value = irace.write(cs)
self.assertEqual(expected, value)
def test_write_equals_condition_categorical(self):
expected = "ls '--ls ' c {sa,ca,ny}\ntemp '--temp ' r (0.500000, 1.000000)| ls==sa\n"
temp = UniformFloatHyperparameter("temp", 0.5, 1)
ls = CategoricalHyperparameter("ls", ["sa", "ca", "ny"], "sa")
cs = ConfigurationSpace()
cs.add_hyperparameter(temp)
cs.add_hyperparameter(ls)
c1 = EqualsCondition(temp, ls, 'sa')
cs.add_condition(c1)
value = irace.write(cs)
self.assertEqual(expected, value)
def test_equals_condition(self):
hp1 = CategoricalHyperparameter("parent", [0, 1])
hp2 = UniformIntegerHyperparameter("child", 0, 10)
cond = EqualsCondition(hp2, hp1, 0)
cond_ = EqualsCondition(hp2, hp1, 0)
# Test vector value:
self.assertEqual(cond.vector_value, hp1._inverse_transform(0))
self.assertEqual(cond.vector_value, cond_.vector_value)
# Test invalid conditions:
self.assertRaises(TypeError, EqualsCondition, hp2, "parent", 0)
self.assertRaises(TypeError, EqualsCondition, "child", hp1, 0)
self.assertRaises(ValueError, EqualsCondition, hp1, hp1, 0)
self.assertEqual(cond, cond_)
cond_reverse = EqualsCondition(hp1, hp2, 0)
self.assertNotEqual(cond, cond_reverse)
self.assertNotEqual(cond, dict())
self.assertEqual("child | parent == 0", str(cond))
def test_nested_conjunctions(self):
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")
cond1 = EqualsCondition(hp6, hp1, 1)
cond2 = EqualsCondition(hp6, hp2, 1)
cond3 = EqualsCondition(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)
# TODO: this does not look nice, And should depend on a large
# conjunction, there should not be many ANDs inside this string!
self.assertEqual(
"(((AND | input1 == 1 && AND | input2 == 1) || AND | "
"input3 == 1) && AND | input4 == 1 && AND | input5 "
"== 1)", str(conj3))
def test_write_OrConjunction_condition(self):
import numpy as np
expected = "lp '--lp ' c {mi,bo}\ntemp '--temp ' r (2.000000, 5.000000)\nls '--ls ' c {sa,ca,ny}| temp==3.0 || lp %in% c(bo)\n"
temp = UniformFloatHyperparameter("temp",
np.exp(2),
np.exp(5),
log=True)
ls = CategoricalHyperparameter("ls", ["sa", "ca", "ny"], "sa")
lp = CategoricalHyperparameter("lp", ["mi", "bo"], "bo")
cs = ConfigurationSpace()
cs.add_hyperparameter(temp)
cs.add_hyperparameter(lp)
cs.add_hyperparameter(ls)
c1 = EqualsCondition(ls, temp, np.exp(3))
c2 = InCondition(ls, lp, ['bo'])
c3 = OrConjunction(c1, c2)
cs.add_condition(c3)
value = irace.write(cs)
self.assertEqual(expected, value)
def read(pcs_string, debug=False):
configuration_space = ConfigurationSpace()
conditions = []
forbidden = []
# some statistics
ct = 0
cont_ct = 0
cat_ct = 0
line_ct = 0
for line in pcs_string:
line_ct += 1
if "#" in line:
# It contains a comment
pos = line.find("#")
line = line[:pos]
# Remove quotes and whitespaces at beginning and end
ori_line = line
line = line.replace('"', "").replace("'", "")
line = line.strip()
if "|" in line:
# It's a condition
try:
c = pp_condition.parseString(line)
conditions.append(c)
except pyparsing.ParseException:
raise NotImplementedError("Could not parse condition: %s" %
line)
continue
if "}" not in line and "]" not in line:
continue
if line.startswith("{") and line.endswith("}"):
forbidden.append(line)
continue
if len(line.strip()) == 0:
continue
ct += 1
param = None
create = {
"int": UniformIntegerHyperparameter,
"float": UniformFloatHyperparameter,
"categorical": CategoricalHyperparameter
}
try:
param_list = pp_cont_param.parseString(line)
il = param_list[9:]
if len(il) > 0:
il = il[0]
param_list = param_list[:9]
name = param_list[0]
lower = float(param_list[2])
upper = float(param_list[4])
paramtype = "int" if "i" in il else "float"
log = True if "l" in il else False
default_value = float(param_list[7])
param = create[paramtype](name=name,
lower=lower,
upper=upper,
q=None,
log=log,
default_value=default_value)
cont_ct += 1
except pyparsing.ParseException:
pass
try:
param_list = pp_cat_param.parseString(line)
name = param_list[0]
#choices = [c for c in param_list[2:-4:2]]
ori_line_segs = ori_line.split('{')
choices_str = '[' + ori_line_segs[1].split('}')[0] + ']'
choices = json.loads(choices_str)
#default_value = param_list[-2]
ori_line_segs = ori_line.split('[')
default_str = ori_line_segs[-1].split(']')[0]
default_value = json.loads(default_str)
param = create["categorical"](name=name,
choices=choices,
default_value=default_value)
cat_ct += 1
except pyparsing.ParseException:
pass
if param is None:
raise NotImplementedError("Could not parse: %s" % line)
configuration_space.add_hyperparameter(param)
for clause in forbidden:
# TODO test this properly!
# TODO Add a try/catch here!
# noinspection PyUnusedLocal
param_list = pp_forbidden_clause.parseString(clause)
tmp_list = []
clause_list = []
for value in param_list[1:]:
if len(tmp_list) < 3:
tmp_list.append(value)
else:
# So far, only equals is supported by SMAC
if tmp_list[1] == '=':
# TODO maybe add a check if the hyperparameter is
# actually in the configuration space
clause_list.append(
ForbiddenEqualsClause(
configuration_space.get_hyperparameter(
tmp_list[0]), tmp_list[2]))
else:
raise NotImplementedError()
tmp_list = []
configuration_space.add_forbidden_clause(
ForbiddenAndConjunction(*clause_list))
#Now handle conditions
# If there are two conditions for one child, these two conditions are an
# AND-conjunction of conditions, thus we have to connect them
conditions_per_child = OrderedDict()
for condition in conditions:
child_name = condition[0]
if child_name not in conditions_per_child:
conditions_per_child[child_name] = list()
conditions_per_child[child_name].append(condition)
for child_name in conditions_per_child:
condition_objects = []
for condition in conditions_per_child[child_name]:
child = configuration_space.get_hyperparameter(child_name)
parent_name = condition[2]
parent = configuration_space.get_hyperparameter(parent_name)
restrictions = condition[5:-1:2]
# TODO: cast the type of the restriction!
if len(restrictions) == 1:
condition = EqualsCondition(child, parent, restrictions[0])
else:
condition = InCondition(child, parent, values=restrictions)
condition_objects.append(condition)
# Now we have all condition objects for this child, so we can build a
# giant AND-conjunction of them (if number of conditions >= 2)!
if len(condition_objects) > 1:
and_conjunction = AndConjunction(*condition_objects)
configuration_space.add_condition(and_conjunction)
else:
configuration_space.add_condition(condition_objects[0])
return configuration_space
def test_read_new_configuration_space_complex_conditionals(self):
classi = OrdinalHyperparameter("classi", [
"random_forest", "extra_trees", "k_nearest_neighbors", "something"
])
knn_weights = CategoricalHyperparameter("knn_weights",
["uniform", "distance"])
weather = OrdinalHyperparameter(
"weather", ["sunny", "rainy", "cloudy", "snowing"])
temperature = CategoricalHyperparameter("temperature", ["high", "low"])
rain = CategoricalHyperparameter("rain", ["yes", "no"])
gloves = OrdinalHyperparameter("gloves",
["none", "yarn", "leather", "gortex"])
heur1 = CategoricalHyperparameter("heur1", ["off", "on"])
heur2 = CategoricalHyperparameter("heur2", ["off", "on"])
heur_order = CategoricalHyperparameter("heur_order",
["heur1then2", "heur2then1"])
gloves_condition = OrConjunction(
EqualsCondition(gloves, rain, "yes"),
EqualsCondition(gloves, temperature, "low"))
heur_condition = AndConjunction(
EqualsCondition(heur_order, heur1, "on"),
EqualsCondition(heur_order, heur2, "on"))
and_conjunction = AndConjunction(
NotEqualsCondition(knn_weights, classi, "extra_trees"),
EqualsCondition(knn_weights, classi, "random_forest"))
Cl_condition = OrConjunction(
EqualsCondition(knn_weights, classi, "k_nearest_neighbors"),
and_conjunction, EqualsCondition(knn_weights, classi, "something"))
and1 = AndConjunction(EqualsCondition(temperature, weather, "rainy"),
EqualsCondition(temperature, weather, "cloudy"))
and2 = AndConjunction(
EqualsCondition(temperature, weather, "sunny"),
NotEqualsCondition(temperature, weather, "snowing"))
another_condition = OrConjunction(and1, and2)
complex_conditional_space = ConfigurationSpace()
complex_conditional_space.add_hyperparameter(classi)
complex_conditional_space.add_hyperparameter(knn_weights)
complex_conditional_space.add_hyperparameter(weather)
complex_conditional_space.add_hyperparameter(temperature)
complex_conditional_space.add_hyperparameter(rain)
complex_conditional_space.add_hyperparameter(gloves)
complex_conditional_space.add_hyperparameter(heur1)
complex_conditional_space.add_hyperparameter(heur2)
complex_conditional_space.add_hyperparameter(heur_order)
complex_conditional_space.add_condition(gloves_condition)
complex_conditional_space.add_condition(heur_condition)
complex_conditional_space.add_condition(Cl_condition)
complex_conditional_space.add_condition(another_condition)
complex_cs = list()
complex_cs.append(
"classi ordinal {random_forest,extra_trees,k_nearest_neighbors, something} [random_forest]"
)
complex_cs.append(
"knn_weights categorical {uniform, distance} [uniform]")
complex_cs.append(
"weather ordinal {sunny, rainy, cloudy, snowing} [sunny]")
complex_cs.append("temperature categorical {high, low} [high]")
complex_cs.append("rain categorical { yes, no } [yes]")
complex_cs.append(
"gloves ordinal { none, yarn, leather, gortex } [none]")
complex_cs.append("heur1 categorical { off, on } [off]")
complex_cs.append("heur2 categorical { off, on } [off]")
complex_cs.append(
"heur_order categorical { heur1then2, heur2then1 } [heur1then2]")
complex_cs.append("gloves | rain == yes || temperature == low")
complex_cs.append("heur_order | heur1 == on && heur2 == on")
complex_cs.append(
"knn_weights | classi == k_nearest_neighbors || classi != extra_trees && classi == random_forest || classi == something"
)
complex_cs.append(
"temperature | weather == rainy && weather == cloudy || weather == sunny && weather != snowing"
)
cs_new = pcs_new.read(complex_cs)
self.assertEqual(cs_new, complex_conditional_space)
import unittest
from ConfigSpaceNNI.configuration_space import ConfigurationSpace
import ConfigSpaceNNI.read_and_write.pcs as pcs
import ConfigSpaceNNI.read_and_write.pcs_new as pcs_new
from ConfigSpaceNNI.hyperparameters import CategoricalHyperparameter, \
UniformIntegerHyperparameter, UniformFloatHyperparameter, OrdinalHyperparameter
from ConfigSpaceNNI.conditions import EqualsCondition, InCondition, \
AndConjunction, OrConjunction, NotEqualsCondition, \
GreaterThanCondition
from ConfigSpaceNNI.forbidden import ForbiddenInClause, ForbiddenAndConjunction
# More complex search space
classifier = CategoricalHyperparameter("classifier", ["svm", "nn"])
kernel = CategoricalHyperparameter("kernel", ["rbf", "poly", "sigmoid"])
kernel_condition = EqualsCondition(kernel, classifier, "svm")
C = UniformFloatHyperparameter("C", 0.03125, 32768, log=True)
C_condition = EqualsCondition(C, classifier, "svm")
gamma = UniformFloatHyperparameter("gamma", 0.000030518, 8, log=True)
gamma_condition = EqualsCondition(gamma, kernel, "rbf")
degree = UniformIntegerHyperparameter("degree", 1, 5)
degree_condition = InCondition(degree, kernel, ["poly", "sigmoid"])
neurons = UniformIntegerHyperparameter("neurons", 16, 1024)
neurons_condition = EqualsCondition(neurons, classifier, "nn")
lr = UniformFloatHyperparameter("lr", 0.0001, 1.0)
lr_condition = EqualsCondition(lr, classifier, "nn")
preprocessing = CategoricalHyperparameter("preprocessing", ["None", "pca"])
conditional_space = ConfigurationSpace()
conditional_space.add_hyperparameter(preprocessing)
conditional_space.add_hyperparameter(classifier)
conditional_space.add_hyperparameter(kernel)