def test___init___users_values(self, mock_super):
# setup
tunable = MagicMock(spec_set=Tunable)
instance = MagicMock()
instance._metamodel_kwargs = {'a': 'test'}
instance._acquisition_kwargs = {'a': 'acquisition_test'}
instance.__init_metamodel__ = MagicMock()
instance.__init_acquisition__ = MagicMock()
# run
BaseMetaModelTuner.__init__(
instance,
tunable,
maximize=False,
num_candidates=5,
min_trials=20,
)
# assert
assert instance.num_candidates == 5
assert instance.min_trials == 20
instance.__init_metamodel__.assert_called_once_with(a='test')
instance.__init_acquisition__.assert_called_once_with(
a='acquisition_test')
def test_record(self, mock_super):
# setup
instance = MagicMock()
instance.trials = np.array([2])
instance.scores = 1
instance.min_trials = 1
# run
BaseMetaModelTuner.record(instance, 1, 1)
# assert
mock_super.return_value.record.assert_called_once_with(1, 1)
instance._fit.assert_called_once_with(np.array([2]), 1)
def test___init___default_values(self, mock_super):
# setup
tunable = MagicMock(spec_set=Tunable)
instance = MagicMock()
instance.__init_metamodel__ = MagicMock()
instance.__init_acquisition__ = MagicMock()
# run
BaseMetaModelTuner.__init__(instance, tunable)
# assert
assert instance.num_candidates == 1000
assert instance.min_trials == 5
instance.__init_metamodel__.assert_called_once_with()
instance.__init_acquisition__.assert_called_once_with()
def test__proposemin_trials_gt__trials_set(self):
# setup
instance = MagicMock()
instance.min_trials = 1
instance._trials_set.__len__.return_value = 0
instance._sample.return_value = 'sample'
# run
result = BaseMetaModelTuner._propose(instance, 1, True)
# assert
instance._sample.assert_called_once_with(1, True)
assert result == 'sample'
def test__propose_min_trials_lt__trials_set_allow_duplicates(self):
# setup
instance = MagicMock()
instance.tunable.cardinality = 3
instance._min_trials = 0
instance._num_candidates = 10
instance._trials_set.__len__.return_value = 1
instance._sample.return_value = np.array([1])
instance._predict.return_value = 'predicted'
instance._acquire.return_value = 0
# run
result = BaseMetaModelTuner._propose(instance, 1, True)
# assert
instance._sample.assert_called_once_with(10, True)
instance._predict.assert_called_once_with(np.array([1]))
assert result == 1