def testRoundingWithImpossiblyConstrainedIntRanges(self):
parameters = [
RangeParameter("x",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
RangeParameter("y",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
]
constrained_int_search_space = SearchSpace(
parameters=parameters,
parameter_constraints=[
SumConstraint(parameters=parameters,
is_upper_bound=True,
bound=3)
],
)
t = IntToFloat(
search_space=constrained_int_search_space,
observation_features=None,
observation_data=None,
)
self.assertEqual(t.rounding, "randomized")
observation_features = [
ObservationFeatures(parameters={
"x": 2.6,
"y": 2.6
})
]
self.assertFalse(
constrained_int_search_space.check_membership(
t.untransform_observation_features(
observation_features=observation_features)[0].parameters))
def setUp(self):
self.search_space = SearchSpace(
parameters=[
RangeParameter("x",
lower=1,
upper=3,
parameter_type=ParameterType.FLOAT),
RangeParameter("a",
lower=1,
upper=2,
parameter_type=ParameterType.INT),
RangeParameter("d",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
ChoiceParameter("b",
parameter_type=ParameterType.STRING,
values=["a", "b", "c"]),
],
parameter_constraints=[
ParameterConstraint(constraint_dict={
"x": -0.5,
"a": 1
},
bound=0.5)
],
)
self.t = IntToFloat(
search_space=self.search_space,
observation_features=None,
observation_data=None,
)
self.t2 = IntToFloat(
search_space=self.search_space,
observation_features=None,
observation_data=None,
config={"rounding": "randomized"},
)
def setUp(self):
parameters = [
RangeParameter("x",
lower=1,
upper=3,
parameter_type=ParameterType.FLOAT),
RangeParameter("a",
lower=1,
upper=2,
parameter_type=ParameterType.INT),
RangeParameter("d",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
ChoiceParameter("b",
parameter_type=ParameterType.STRING,
values=["a", "b", "c"]),
]
self.search_space = SearchSpace(
parameters=parameters,
parameter_constraints=[
OrderConstraint(lower_parameter=parameters[0],
upper_parameter=parameters[1])
],
)
self.t = IntToFloat(
search_space=self.search_space,
observation_features=None,
observation_data=None,
)
self.t2 = IntToFloat(
search_space=self.search_space,
observation_features=None,
observation_data=None,
config={"rounding": "randomized"},
)
class IntToFloatTransformTest(TestCase):
def setUp(self):
self.search_space = SearchSpace(
parameters=[
RangeParameter("x",
lower=1,
upper=3,
parameter_type=ParameterType.FLOAT),
RangeParameter("a",
lower=1,
upper=2,
parameter_type=ParameterType.INT),
RangeParameter("d",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
ChoiceParameter("b",
parameter_type=ParameterType.STRING,
values=["a", "b", "c"]),
],
parameter_constraints=[
ParameterConstraint(constraint_dict={
"x": -0.5,
"a": 1
},
bound=0.5)
],
)
self.t = IntToFloat(
search_space=self.search_space,
observation_features=None,
observation_data=None,
)
self.t2 = IntToFloat(
search_space=self.search_space,
observation_features=None,
observation_data=None,
config={"rounding": "randomized"},
)
def testInit(self):
self.assertEqual(self.t.transform_parameters, {"a", "d"})
def testTransformObservationFeatures(self):
observation_features = [
ObservationFeatures(parameters={
"x": 2.2,
"a": 2,
"b": "b",
"d": 4
})
]
obs_ft2 = deepcopy(observation_features)
obs_ft2 = self.t.transform_observation_features(obs_ft2)
self.assertEqual(
obs_ft2,
[
ObservationFeatures(parameters={
"x": 2.2,
"a": 2,
"b": "b",
"d": 4
})
],
)
self.assertTrue(isinstance(obs_ft2[0].parameters["a"], float))
self.assertTrue(isinstance(obs_ft2[0].parameters["d"], float))
obs_ft2 = self.t.untransform_observation_features(obs_ft2)
self.assertEqual(obs_ft2, observation_features)
# Let the transformed space be a float, verify it becomes an int.
obs_ft3 = [
ObservationFeatures(parameters={
"x": 2.2,
"a": 2.2,
"b": "b",
"d": 3.8
})
]
obs_ft3 = self.t.untransform_observation_features(obs_ft3)
self.assertEqual(obs_ft3, observation_features)
# Test forward transform on partial observation
obs_ft4 = [ObservationFeatures(parameters={"x": 2.2, "d": 4})]
obs_ft4 = self.t.transform_observation_features(obs_ft4)
self.assertEqual(obs_ft4,
[ObservationFeatures(parameters={
"x": 2.2,
"d": 4
})])
self.assertTrue(isinstance(obs_ft4[0].parameters["d"], float))
obs_ft5 = self.t.transform_observation_features(
[ObservationFeatures({})])
self.assertEqual(obs_ft5[0], ObservationFeatures({}))
def testTransformObservationFeaturesRandomized(self):
observation_features = [
ObservationFeatures(parameters={
"x": 2.2,
"a": 2,
"b": "b",
"d": 4
})
]
obs_ft2 = deepcopy(observation_features)
obs_ft2 = self.t2.transform_observation_features(obs_ft2)
self.assertEqual(
obs_ft2,
[
ObservationFeatures(parameters={
"x": 2.2,
"a": 2,
"b": "b",
"d": 4
})
],
)
self.assertTrue(isinstance(obs_ft2[0].parameters["a"], float))
self.assertTrue(isinstance(obs_ft2[0].parameters["d"], float))
obs_ft2 = self.t2.untransform_observation_features(obs_ft2)
self.assertEqual(obs_ft2, observation_features)
def testTransformSearchSpace(self):
ss2 = deepcopy(self.search_space)
ss2 = self.t.transform_search_space(ss2)
self.assertTrue(ss2.parameters["a"].parameter_type,
ParameterType.FLOAT)
self.assertTrue(ss2.parameters["d"].parameter_type,
ParameterType.FLOAT)
class IntToFloatTransformTest(TestCase):
def setUp(self):
parameters = [
RangeParameter("x",
lower=1,
upper=3,
parameter_type=ParameterType.FLOAT),
RangeParameter("a",
lower=1,
upper=2,
parameter_type=ParameterType.INT),
RangeParameter("d",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
ChoiceParameter("b",
parameter_type=ParameterType.STRING,
values=["a", "b", "c"]),
]
self.search_space = SearchSpace(
parameters=parameters,
parameter_constraints=[
OrderConstraint(lower_parameter=parameters[0],
upper_parameter=parameters[1])
],
)
self.t = IntToFloat(
search_space=self.search_space,
observation_features=None,
observation_data=None,
)
self.t2 = IntToFloat(
search_space=self.search_space,
observation_features=None,
observation_data=None,
config={"rounding": "randomized"},
)
def testInit(self):
self.assertEqual(self.t.transform_parameters, {"a", "d"})
def testTransformObservationFeatures(self):
observation_features = [
ObservationFeatures(parameters={
"x": 2.2,
"a": 2,
"b": "b",
"d": 4
})
]
obs_ft2 = deepcopy(observation_features)
obs_ft2 = self.t.transform_observation_features(obs_ft2)
self.assertEqual(
obs_ft2,
[
ObservationFeatures(parameters={
"x": 2.2,
"a": 2,
"b": "b",
"d": 4
})
],
)
self.assertTrue(isinstance(obs_ft2[0].parameters["a"], float))
self.assertTrue(isinstance(obs_ft2[0].parameters["d"], float))
obs_ft2 = self.t.untransform_observation_features(obs_ft2)
self.assertEqual(obs_ft2, observation_features)
# Let the transformed space be a float, verify it becomes an int.
obs_ft3 = [
ObservationFeatures(parameters={
"x": 2.2,
"a": 2.2,
"b": "b",
"d": 3.8
})
]
obs_ft3 = self.t.untransform_observation_features(obs_ft3)
self.assertEqual(obs_ft3, observation_features)
# Test forward transform on partial observation
obs_ft4 = [ObservationFeatures(parameters={"x": 2.2, "d": 4})]
obs_ft4 = self.t.transform_observation_features(obs_ft4)
self.assertEqual(obs_ft4,
[ObservationFeatures(parameters={
"x": 2.2,
"d": 4
})])
self.assertTrue(isinstance(obs_ft4[0].parameters["d"], float))
obs_ft5 = self.t.transform_observation_features(
[ObservationFeatures({})])
self.assertEqual(obs_ft5[0], ObservationFeatures({}))
def testTransformObservationFeaturesRandomized(self):
observation_features = [
ObservationFeatures(parameters={
"x": 2.2,
"a": 2,
"b": "b",
"d": 4
})
]
obs_ft2 = deepcopy(observation_features)
obs_ft2 = self.t2.transform_observation_features(obs_ft2)
self.assertEqual(
obs_ft2,
[
ObservationFeatures(parameters={
"x": 2.2,
"a": 2,
"b": "b",
"d": 4
})
],
)
self.assertTrue(isinstance(obs_ft2[0].parameters["a"], float))
self.assertTrue(isinstance(obs_ft2[0].parameters["d"], float))
obs_ft2 = self.t2.untransform_observation_features(obs_ft2)
self.assertEqual(obs_ft2, observation_features)
def testTransformSearchSpace(self):
ss2 = deepcopy(self.search_space)
ss2 = self.t.transform_search_space(ss2)
self.assertTrue(ss2.parameters["a"].parameter_type,
ParameterType.FLOAT)
self.assertTrue(ss2.parameters["d"].parameter_type,
ParameterType.FLOAT)
def testRoundingWithConstrainedIntRanges(self):
parameters = [
RangeParameter("x",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
RangeParameter("y",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
]
constrained_int_search_space = SearchSpace(
parameters=parameters,
parameter_constraints=[
SumConstraint(parameters=parameters,
is_upper_bound=True,
bound=5)
],
)
t = IntToFloat(
search_space=constrained_int_search_space,
observation_features=None,
observation_data=None,
)
self.assertEqual(t.rounding, "randomized")
observation_features = [
ObservationFeatures(parameters={
"x": 2.6,
"y": 2.6
})
]
self.assertTrue(
constrained_int_search_space.check_membership(
t.untransform_observation_features(
observation_features=observation_features)[0].parameters))
def testRoundingWithImpossiblyConstrainedIntRanges(self):
parameters = [
RangeParameter("x",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
RangeParameter("y",
lower=1,
upper=3,
parameter_type=ParameterType.INT),
]
constrained_int_search_space = SearchSpace(
parameters=parameters,
parameter_constraints=[
SumConstraint(parameters=parameters,
is_upper_bound=True,
bound=3)
],
)
t = IntToFloat(
search_space=constrained_int_search_space,
observation_features=None,
observation_data=None,
)
self.assertEqual(t.rounding, "randomized")
observation_features = [
ObservationFeatures(parameters={
"x": 2.6,
"y": 2.6
})
]
self.assertFalse(
constrained_int_search_space.check_membership(
t.untransform_observation_features(
observation_features=observation_features)[0].parameters))
