def test_random_search_tuner_basic(dummy_pipeline_hyperparameters,
dummy_pipeline_hyperparameters_unicode):
tuner = RandomSearchTuner(dummy_pipeline_hyperparameters, random_seed=random_seed)
proposed_params = tuner.propose()
assert proposed_params == {
'Mock Classifier': {
'param a': 5,
'param b': 8.442657485810175,
'param c': 'option c',
'param d': np.inf
}
}
tuner.add(proposed_params, 0.5)
tuner = RandomSearchTuner(dummy_pipeline_hyperparameters_unicode, random_seed=random_seed)
proposed_params = tuner.propose()
assert proposed_params == {
'Mock Classifier': {
'param a': 5,
'param b': 8.442657485810175,
'param c': 'option c 💩',
'param d': np.inf
}
}
tuner.add(proposed_params, 0.5)
def test_random_search_tuner_space_types():
tuner = RandomSearchTuner({'Mock Classifier': {
'param a': (0, 10)
}},
random_seed=random_seed)
proposed_params = tuner.propose()
assert proposed_params == {'Mock Classifier': {'param a': 5}}
tuner = RandomSearchTuner({'Mock Classifier': {
'param a': (0, 10.0)
}},
random_seed=random_seed)
proposed_params = tuner.propose()
assert proposed_params == {
'Mock Classifier': {
'param a': 5.488135039273248
}
}
tuner = RandomSearchTuner({'Mock Classifier': {
'param a': 10.0
}},
random_seed=random_seed)
proposed_params = tuner.propose()
assert proposed_params == {'Mock Classifier': {}}
def test_random_search_tuner_no_params(dummy_pipeline_hyperparameters_small):
tuner = RandomSearchTuner(dummy_pipeline_hyperparameters_small,
random_seed=random_seed,
with_replacement=False)
error_text = "Cannot create a unique set of unexplored parameters. Try expanding the search space."
with pytest.raises(NoParamsException, match=error_text):
for i in range(10):
tuner.propose()
def test_random_search_tuner_with_replacement(dummy_pipeline_hyperparameters):
tuner = RandomSearchTuner(dummy_pipeline_hyperparameters, random_seed=random_seed, with_replacement=True)
for i in range(10):
proposal = tuner.propose()
assert isinstance(proposal, dict)
assert proposal.keys() == dummy_pipeline_hyperparameters.keys()
assert proposal['Mock Classifier'].keys() == dummy_pipeline_hyperparameters['Mock Classifier'].keys()
def test_random_search_tuner_unique_values(dummy_pipeline_hyperparameters):
tuner = RandomSearchTuner(dummy_pipeline_hyperparameters, random_seed=random_seed)
generated_parameters = []
for i in range(3):
params = tuner.propose()
generated_parameters.append(params)
assert len(generated_parameters) == 3
for i in range(3):
assert generated_parameters[i].keys() == dummy_pipeline_hyperparameters.keys()
assert generated_parameters[i]['Mock Classifier'].keys() == dummy_pipeline_hyperparameters['Mock Classifier'].keys()