def test_skopt_tuner_basic():
pipeline_hyperparameter_ranges = {
'Mock Classifier': {
'parameter a': Integer(0, 10),
'parameter b': Real(0, 10),
'parameter c': (0, 10),
'parameter d': (0, 10.0),
'parameter e': ['option a', 'option b', 'option c'],
'parameter f': ['option a 💩', 'option b 💩', 'option c 💩'],
'parameter g': ['option a', 'option b', 100, np.inf]
}
}
tuner = SKOptTuner(pipeline_hyperparameter_ranges, random_seed=random_seed)
assert isinstance(tuner, Tuner)
proposed_params = tuner.propose()
assert proposed_params == {
'Mock Classifier': {
'parameter a': 5,
'parameter b': 8.442657485810175,
'parameter c': 3,
'parameter d': 8.472517387841256,
'parameter e': 'option b',
'parameter f': 'option b 💩',
'parameter g': 'option b'
}
}
tuner.add(proposed_params, 0.5)
def test_skopt_tuner_propose():
pipeline_hyperparameter_ranges = {
'Mock Classifier': {
'param a': Integer(0, 10),
'param b': Real(0, 10),
'param c': ['option a', 'option b', 'option c']
}
}
tuner = SKOptTuner(pipeline_hyperparameter_ranges, random_seed=random_seed)
tuner.add(
{
'Mock Classifier': {
'param a': 0,
'param b': 1.0,
'param c': 'option a'
}
}, 0.5)
parameters = tuner.propose()
assert parameters == {
'Mock Classifier': {
'param a': 5,
'param b': 8.442657485810175,
'param c': 'option c'
}
}
def test_skopt_tuner_single_value():
SKOptTuner({'Mock Classifier': {
'param a': Integer(0, 10),
'param b': Real(0, 10),
'param c': 'Value'
}}, random_state=random_state)
tuner = SKOptTuner({'Mock Classifier': {
'param c': 10
}}, random_state=random_state)
proposed_params = tuner.propose()
assert proposed_params == {'Mock Classifier': {}}
def test_skopt_tuner_invalid_parameters_score():
pipeline_hyperparameter_ranges = {'Mock Classifier': {
'param a': Integer(0, 10),
'param b': Real(0, 10),
'param c': ['option a', 'option b', 'option c']
}}
tuner = SKOptTuner(pipeline_hyperparameter_ranges, random_state=random_state)
with pytest.raises(TypeError, match='Pipeline parameters missing required field "param a" for component "Mock Classifier"'):
tuner.add({}, 0.5)
with pytest.raises(TypeError, match='Pipeline parameters missing required field "param a" for component "Mock Classifier"'):
tuner.add({'Mock Classifier': {}}, 0.5)
with pytest.raises(TypeError, match='Pipeline parameters missing required field "param b" for component "Mock Classifier"'):
tuner.add({'Mock Classifier': {'param a': 0}}, 0.5)
with pytest.raises(ValueError, match="is not within the bounds of the space"):
tuner.add({'Mock Classifier': {'param a': 0, 'param b': 0.0, 'param c': 0}}, 0.5)
with pytest.raises(ValueError, match="is not within the bounds of the space"):
tuner.add({'Mock Classifier': {'param a': -1, 'param b': 0.0, 'param c': 'option a'}}, 0.5)
with pytest.raises(ValueError, match="is not within the bounds of the space"):
tuner.add({'Mock Classifier': {'param a': 0, 'param b': 11.0, 'param c': 'option a'}}, 0.5)
with pytest.raises(ValueError, match="is not within the bounds of the space"):
tuner.add({'Mock Classifier': {'param a': 0, 'param b': 0.0, 'param c': 'option d'}}, 0.5)
with pytest.raises(ValueError, match="is not within the bounds of the space"):
tuner.add({'Mock Classifier': {'param a': np.nan, 'param b': 0.0, 'param c': 'option a'}}, 0.5)
with pytest.raises(ValueError, match="is not within the bounds of the space"):
tuner.add({'Mock Classifier': {'param a': np.inf, 'param b': 0.0, 'param c': 'option a'}}, 0.5)
with pytest.raises(ParameterError, match="Invalid parameters specified to SKOptTuner.add"):
tuner.add({'Mock Classifier': {'param a': None, 'param b': 0.0, 'param c': 'option a'}}, 0.5)
with patch('evalml.tuners.skopt_tuner.Optimizer.tell') as mock_optimizer_tell:
msg = 'Mysterious internal error'
mock_optimizer_tell.side_effect = Exception(msg)
with pytest.raises(Exception, match=msg):
tuner.add({'Mock Classifier': {'param a': 0, 'param b': 0.0, 'param c': 'option a'}}, 0.5)
tuner.add({'Mock Classifier': {'param a': 0, 'param b': 1.0, 'param c': 'option a'}}, 0.5)
tuner.add({'Mock Classifier': {'param a': 0, 'param b': 1.0, 'param c': 'option a'}}, np.nan)
tuner.add({'Mock Classifier': {'param a': 0, 'param b': 1.0, 'param c': 'option a'}}, np.inf)
tuner.add({'Mock Classifier': {'param a': 0, 'param b': 1.0, 'param c': 'option a'}}, None)
tuner.propose()