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from typing import Callable
from typing import Generator
from typing import Optional
from unittest import mock
from _pytest.logging import LogCaptureFixture
import pytest
from optuna import create_study
from optuna import logging
from optuna import Trial
from optuna import TrialPruned
from optuna.study import _optimize
from optuna.study._tell import _tell_with_warning
from optuna.study._tell import STUDY_TELL_WARNING_KEY
from optuna.testing.objectives import fail_objective
from optuna.testing.storages import STORAGE_MODES
from optuna.testing.storages import StorageSupplier
from optuna.trial import TrialState
@pytest.fixture(autouse=True)
def logging_setup() -> Generator[None, None, None]:
# We need to reconstruct our default handler to properly capture stderr.
logging._reset_library_root_logger()
logging.enable_default_handler()
logging.set_verbosity(logging.INFO)
logging.enable_propagation()
yield
# After testing, restore default propagation setting.
logging.disable_propagation()
@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
def test_run_trial(storage_mode: str, caplog: LogCaptureFixture) -> None:
with StorageSupplier(storage_mode) as storage:
study = create_study(storage=storage)
caplog.clear()
frozen_trial = _optimize._run_trial(study, lambda _: 1.0, catch=())
assert frozen_trial.state == TrialState.COMPLETE
assert frozen_trial.value == 1.0
assert "Trial 0 finished with value: 1.0 and parameters" in caplog.text
caplog.clear()
frozen_trial = _optimize._run_trial(study, lambda _: float("inf"), catch=())
assert frozen_trial.state == TrialState.COMPLETE
assert frozen_trial.value == float("inf")
assert "Trial 1 finished with value: inf and parameters" in caplog.text
caplog.clear()
frozen_trial = _optimize._run_trial(study, lambda _: -float("inf"), catch=())
assert frozen_trial.state == TrialState.COMPLETE
assert frozen_trial.value == -float("inf")
assert "Trial 2 finished with value: -inf and parameters" in caplog.text
@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
def test_run_trial_automatically_fail(storage_mode: str, caplog: LogCaptureFixture) -> None:
with StorageSupplier(storage_mode) as storage:
study = create_study(storage=storage)
frozen_trial = _optimize._run_trial(study, lambda _: float("nan"), catch=())
assert frozen_trial.state == TrialState.FAIL
assert frozen_trial.value is None
frozen_trial = _optimize._run_trial(study, lambda _: None, catch=()) # type: ignore[arg-type,return-value] # noqa: E501
assert frozen_trial.state == TrialState.FAIL
assert frozen_trial.value is None
frozen_trial = _optimize._run_trial(study, lambda _: object(), catch=()) # type: ignore[arg-type,return-value] # noqa: E501
assert frozen_trial.state == TrialState.FAIL
assert frozen_trial.value is None
frozen_trial = _optimize._run_trial(study, lambda _: [0, 1], catch=())
assert frozen_trial.state == TrialState.FAIL
assert frozen_trial.value is None
@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
def test_run_trial_pruned(storage_mode: str, caplog: LogCaptureFixture) -> None:
def gen_func(intermediate: Optional[float] = None) -> Callable[[Trial], float]:
def func(trial: Trial) -> float:
if intermediate is not None:
trial.report(step=1, value=intermediate)
raise TrialPruned
return func
with StorageSupplier(storage_mode) as storage:
study = create_study(storage=storage)
caplog.clear()
frozen_trial = _optimize._run_trial(study, gen_func(), catch=())
assert frozen_trial.state == TrialState.PRUNED
assert frozen_trial.value is None
assert "Trial 0 pruned." in caplog.text
caplog.clear()
frozen_trial = _optimize._run_trial(study, gen_func(intermediate=1), catch=())
assert frozen_trial.state == TrialState.PRUNED
assert frozen_trial.value == 1
assert "Trial 1 pruned." in caplog.text
caplog.clear()
frozen_trial = _optimize._run_trial(study, gen_func(intermediate=float("nan")), catch=())
assert frozen_trial.state == TrialState.PRUNED
assert frozen_trial.value is None
assert "Trial 2 pruned." in caplog.text
@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
def test_run_trial_catch_exception(storage_mode: str) -> None:
with StorageSupplier(storage_mode) as storage:
study = create_study(storage=storage)
frozen_trial = _optimize._run_trial(study, fail_objective, catch=(ValueError,))
assert frozen_trial.state == TrialState.FAIL
assert STUDY_TELL_WARNING_KEY not in frozen_trial.system_attrs
@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
def test_run_trial_exception(storage_mode: str) -> None:
with StorageSupplier(storage_mode) as storage:
study = create_study(storage=storage)
with pytest.raises(ValueError):
_optimize._run_trial(study, fail_objective, ())
# Test trial with unacceptable exception.
with StorageSupplier(storage_mode) as storage:
study = create_study(storage=storage)
with pytest.raises(ValueError):
_optimize._run_trial(study, fail_objective, (ArithmeticError,))
@pytest.mark.parametrize("storage_mode", STORAGE_MODES)
def test_run_trial_invoke_tell_with_suppressing_warning(storage_mode: str) -> None:
def func_numerical(trial: Trial) -> float:
return trial.suggest_float("v", 0, 10)
with StorageSupplier(storage_mode) as storage:
study = create_study(storage=storage)
with mock.patch(
"optuna.study._optimize._tell_with_warning", side_effect=_tell_with_warning
) as mock_obj:
_optimize._run_trial(study, func_numerical, ())
mock_obj.assert_called_once_with(
study=mock.ANY,
trial=mock.ANY,
value_or_values=mock.ANY,
state=mock.ANY,
suppress_warning=True,
)
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