def test_optimization_result_try_get_final_models_for_successful_optimization(
) -> None:
models = {"foo": _PseudoTrainableQuadratic()}
result: OptimizationResult[None] = OptimizationResult(
Ok(Record({"foo": empty_dataset([1], [1])}, models, None)), [])
assert result.try_get_final_models() is models
assert result.try_get_final_model() is models["foo"]
def test_optimization_result_try_get_final_datasets_for_successful_optimization(
) -> None:
data = {"foo": empty_dataset([1], [1])}
result: OptimizationResult[None] = OptimizationResult(
Ok(Record(data, {"foo": _PseudoTrainableQuadratic()}, None)), [])
assert result.try_get_final_datasets() is data
assert result.try_get_final_dataset() is data["foo"]
def test_optimization_result_try_get_final_models_for_multiple_models() -> None:
data = {"foo": empty_dataset([1], [1]), "bar": empty_dataset([2], [2])}
models = {"foo": _PseudoTrainableQuadratic(), "bar": _PseudoTrainableQuadratic()}
result: OptimizationResult[None] = OptimizationResult(Ok(Record(data, models, None)), [])
assert result.try_get_final_models() is models
with pytest.raises(ValueError):
result.try_get_final_model()
def test_optimization_result_astuple() -> None:
opt_result: OptimizationResult[None] = OptimizationResult(
Err(_Whoops()), [Record({}, {}, None)]
)
final_result, history = opt_result.astuple()
assert final_result is opt_result.final_result
assert history is opt_result.history
def test_ask_tell_optimizer_from_state_does_not_train_model(
search_space: Box,
init_dataset: Dataset,
model: TrainableProbabilisticModel,
acquisition_rule: AcquisitionRule[TensorType, Box],
) -> None:
old_state: Record[None] = Record({OBJECTIVE: init_dataset}, {OBJECTIVE: model}, None)
ask_tell = AskTellOptimizer.from_record(old_state, search_space, acquisition_rule)
state_record: Record[None] = ask_tell.to_record()
assert state_record.model.optimize_count == 0 # type: ignore
def test_ask_tell_optimizer_loads_from_state(
search_space: Box,
init_dataset: Dataset,
model: TrainableProbabilisticModel,
acquisition_rule: AcquisitionRule[TensorType, Box],
) -> None:
old_state: Record[None] = Record({OBJECTIVE: init_dataset}, {OBJECTIVE: model}, None)
ask_tell = AskTellOptimizer.from_record(old_state, search_space, acquisition_rule)
new_state: Record[None] = ask_tell.to_record()
assert_datasets_allclose(old_state.dataset, new_state.dataset)
assert isinstance(new_state.model, type(old_state.model))