def _construct_lt_condition(
condition: Dict,
cs: ConfigurationSpace,
) -> LessThanCondition:
return LessThanCondition(
child=cs.get_hyperparameter(condition['child']),
parent=cs.get_hyperparameter(condition['parent']),
value=condition['value'],
)
def test_greater_and_less_condition(self):
child = Constant('child', 'child')
hp1 = UniformFloatHyperparameter("float", 0, 5)
hp2 = UniformIntegerHyperparameter("int", 0, 5)
hp3 = OrdinalHyperparameter("ord", list(range(6)))
for hp in [hp1, hp2, hp3]:
gt = GreaterThanCondition(child, hp, 1)
self.assertFalse(gt.evaluate({hp.name: 0}))
self.assertTrue(gt.evaluate({hp.name: 2}))
self.assertFalse(gt.evaluate({hp.name: None}))
lt = LessThanCondition(child, hp, 1)
self.assertTrue(lt.evaluate({hp.name: 0}))
self.assertFalse(lt.evaluate({hp.name: 2}))
self.assertFalse(lt.evaluate({hp.name: None}))
hp4 = CategoricalHyperparameter("cat", list(range(6)))
self.assertRaisesRegexp(
ValueError, "Parent hyperparameter in a > or < "
"condition must be a subclass of "
"NumericalHyperparameter or "
"OrdinalHyperparameter, but is "
"<class 'ConfigSpace.hyperparameters.CategoricalHyperparameter'>",
GreaterThanCondition, child, hp4, 1)
self.assertRaisesRegexp(
ValueError, "Parent hyperparameter in a > or < "
"condition must be a subclass of "
"NumericalHyperparameter or "
"OrdinalHyperparameter, but is "
"<class 'ConfigSpace.hyperparameters.CategoricalHyperparameter'>",
LessThanCondition, child, hp4, 1)
hp5 = OrdinalHyperparameter("ord",
['cold', 'luke warm', 'warm', 'hot'])
gt = GreaterThanCondition(child, hp5, 'warm')
self.assertTrue(gt.evaluate({hp5.name: 'hot'}))
self.assertFalse(gt.evaluate({hp5.name: 'cold'}))
lt = LessThanCondition(child, hp5, 'warm')
self.assertTrue(lt.evaluate({hp5.name: 'luke warm'}))
self.assertFalse(lt.evaluate({hp5.name: 'warm'}))
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_greater_and_less_condition(self):
child = Constant('child', 'child')
hp1 = UniformFloatHyperparameter("float", 0, 5)
hp2 = UniformIntegerHyperparameter("int", 0, 5)
hp3 = OrdinalHyperparameter("ord", list(range(6)))
for hp in [hp1, hp2, hp3]:
hyperparameter_idx = {child.name: 0, hp.name: 1}
gt = GreaterThanCondition(child, hp, 1)
gt.set_vector_idx(hyperparameter_idx)
self.assertFalse(gt.evaluate({hp.name: 0}))
self.assertTrue(gt.evaluate({hp.name: 2}))
self.assertFalse(gt.evaluate({hp.name: None}))
# Evaluate vector
test_value = hp._inverse_transform(2)
self.assertFalse(gt.evaluate_vector(np.array([np.NaN, 0])))
self.assertTrue(gt.evaluate_vector(np.array([np.NaN, test_value])))
self.assertFalse(gt.evaluate_vector(np.array([np.NaN, np.NaN])))
lt = LessThanCondition(child, hp, 1)
lt.set_vector_idx(hyperparameter_idx)
self.assertTrue(lt.evaluate({hp.name: 0}))
self.assertFalse(lt.evaluate({hp.name: 2}))
self.assertFalse(lt.evaluate({hp.name: None}))
# Evaluate vector
test_value = hp._inverse_transform(2)
self.assertTrue(lt.evaluate_vector(np.array([np.NaN, 0, 0, 0])))
self.assertFalse(lt.evaluate_vector(np.array([np.NaN,
test_value])))
self.assertFalse(lt.evaluate_vector(np.array([np.NaN, np.NaN])))
hp4 = CategoricalHyperparameter("cat", list(range(6)))
self.assertRaisesRegexp(
ValueError, "Parent hyperparameter in a > or < "
"condition must be a subclass of "
"NumericalHyperparameter or "
"OrdinalHyperparameter, but is "
"<class 'ConfigSpace.hyperparameters.CategoricalHyperparameter'>",
GreaterThanCondition, child, hp4, 1)
self.assertRaisesRegexp(
ValueError, "Parent hyperparameter in a > or < "
"condition must be a subclass of "
"NumericalHyperparameter or "
"OrdinalHyperparameter, but is "
"<class 'ConfigSpace.hyperparameters.CategoricalHyperparameter'>",
LessThanCondition, child, hp4, 1)
hp5 = OrdinalHyperparameter("ord",
['cold', 'luke warm', 'warm', 'hot'])
hyperparameter_idx = {child.name: 0, hp5.name: 1}
gt = GreaterThanCondition(child, hp5, 'warm')
gt.set_vector_idx(hyperparameter_idx)
self.assertTrue(gt.evaluate({hp5.name: 'hot'}))
self.assertFalse(gt.evaluate({hp5.name: 'cold'}))
self.assertTrue(gt.evaluate_vector(np.array([np.NaN, 3])))
self.assertFalse(gt.evaluate_vector(np.array([np.NaN, 0])))
lt = LessThanCondition(child, hp5, 'warm')
lt.set_vector_idx(hyperparameter_idx)
self.assertTrue(lt.evaluate({hp5.name: 'luke warm'}))
self.assertFalse(lt.evaluate({hp5.name: 'warm'}))
self.assertTrue(lt.evaluate_vector(np.array([np.NaN, 1])))
self.assertFalse(lt.evaluate_vector(np.array([np.NaN, 2])))
def test_greater_and_less_condition(self):
child = Constant('child', 'child')
hp1 = UniformFloatHyperparameter("float", 0, 5)
hp2 = UniformIntegerHyperparameter("int", 0, 5)
hp3 = OrdinalHyperparameter("ord", list(range(6)))
for hp in [hp1, hp2, hp3]:
hyperparameter_idx = {
child.name: 0,
hp.name: 1
}
gt = GreaterThanCondition(child, hp, 1)
gt.set_vector_idx(hyperparameter_idx)
self.assertFalse(gt.evaluate({hp.name: 0}))
self.assertTrue(gt.evaluate({hp.name: 2}))
self.assertFalse(gt.evaluate({hp.name: None}))
# Evaluate vector
test_value = hp._inverse_transform(2)
self.assertFalse(gt.evaluate_vector(np.array([np.NaN, 0])))
self.assertTrue(gt.evaluate_vector(np.array([np.NaN, test_value])))
self.assertFalse(gt.evaluate_vector(np.array([np.NaN, np.NaN])))
lt = LessThanCondition(child, hp, 1)
lt.set_vector_idx(hyperparameter_idx)
self.assertTrue(lt.evaluate({hp.name: 0}))
self.assertFalse(lt.evaluate({hp.name: 2}))
self.assertFalse(lt.evaluate({hp.name: None}))
# Evaluate vector
test_value = hp._inverse_transform(2)
self.assertTrue(lt.evaluate_vector(np.array([np.NaN, 0, 0, 0])))
self.assertFalse(lt.evaluate_vector(np.array([np.NaN, test_value])))
self.assertFalse(lt.evaluate_vector(np.array([np.NaN, np.NaN])))
hp4 = CategoricalHyperparameter("cat", list(range(6)))
self.assertRaisesRegex(ValueError, "Parent hyperparameter in a > or < "
"condition must be a subclass of "
"NumericalHyperparameter or "
"OrdinalHyperparameter, but is "
"<cdef class 'ConfigSpace.hyperparameters.CategoricalHyperparameter'>",
GreaterThanCondition, child, hp4, 1)
self.assertRaisesRegex(ValueError, "Parent hyperparameter in a > or < "
"condition must be a subclass of "
"NumericalHyperparameter or "
"OrdinalHyperparameter, but is "
"<cdef class 'ConfigSpace.hyperparameters.CategoricalHyperparameter'>",
LessThanCondition, child, hp4, 1)
hp5 = OrdinalHyperparameter("ord", ['cold', 'luke warm', 'warm', 'hot'])
hyperparameter_idx = {
child.name: 0,
hp5.name: 1
}
gt = GreaterThanCondition(child, hp5, 'warm')
gt.set_vector_idx(hyperparameter_idx)
self.assertTrue(gt.evaluate({hp5.name: 'hot'}))
self.assertFalse(gt.evaluate({hp5.name: 'cold'}))
self.assertTrue(gt.evaluate_vector(np.array([np.NaN, 3])))
self.assertFalse(gt.evaluate_vector(np.array([np.NaN, 0])))
lt = LessThanCondition(child, hp5, 'warm')
lt.set_vector_idx(hyperparameter_idx)
self.assertTrue(lt.evaluate({hp5.name: 'luke warm'}))
self.assertFalse(lt.evaluate({hp5.name: 'warm'}))
self.assertTrue(lt.evaluate_vector(np.array([np.NaN, 1])))
self.assertFalse(lt.evaluate_vector(np.array([np.NaN, 2])))
