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_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_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_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_optimization_result_try_get_final_datasets_for_failed_optimization(
) -> None:
result: OptimizationResult[object] = OptimizationResult(Err(_Whoops()), [])
with pytest.raises(_Whoops):
result.try_get_final_datasets()