def objective(trial: optuna.multi_objective.trial.MultiObjectiveTrial) -> List[float]:
if trial.number == 0:
assert trial.suggest_uniform("x", 0, 100) == 2
elif trial.number == 1:
assert trial.suggest_uniform("x", 0, 100) == 3
return [0, 0]
def objective(
trial: optuna.multi_objective.trial.MultiObjectiveTrial,
) -> Tuple[float, float, float]:
if trial.number == 0:
trial.report((1, 2, 3), 1)
trial.report((10, 20, 30), 2)
return 100, 200, 300
def objective(
trial: optuna.multi_objective.trial.MultiObjectiveTrial
) -> List[float]:
return [
trial.suggest_uniform("v{}".format(i), 0, 5)
for i in range(n_objectives)
]
def objective(trial: optuna.multi_objective.trial.MultiObjectiveTrial) -> List[float]:
x = trial.suggest_uniform("x", 0, 10)
assert set(trial.params.keys()) == {"x"}
assert set(trial.distributions.keys()) == {"x"}
assert isinstance(trial.distributions["x"], optuna.distributions.UniformDistribution)
return [x, x, x]
def objective(trial: optuna.multi_objective.trial.MultiObjectiveTrial) -> List[float]:
p0 = trial.suggest_float("p0", -10, 10)
p1 = trial.suggest_uniform("p1", 3, 5)
p2 = trial.suggest_loguniform("p2", 0.00001, 0.1)
p3 = trial.suggest_discrete_uniform("p3", 100, 200, q=5)
p4 = trial.suggest_int("p4", -20, -15)
p5 = trial.suggest_categorical("p5", [7, 1, 100])
p6 = trial.suggest_float("p6", -10, 10, step=1.0)
p7 = trial.suggest_int("p7", 1, 7, log=True)
return [p0 + p1 + p2, p3 + p4 + p5 + p6 + p7]
def objective(trial: optuna.multi_objective.trial.MultiObjectiveTrial) -> Tuple[float, float]:
p0 = trial.suggest_float("p0", -10, 10)
p1 = trial.suggest_float("p1", 3, 5)
p2 = trial.suggest_float("p2", 0.00001, 0.1, log=True)
p3 = trial.suggest_float("p3", 100, 200, step=5)
p4 = trial.suggest_int("p4", -20, -15)
p5 = cast(int, trial.suggest_categorical("p5", [7, 1, 100]))
p6 = trial.suggest_float("p6", -10, 10, step=1.0)
p7 = trial.suggest_int("p7", 1, 7, log=True)
return (
p0 + p1 + p2,
p3 + p4 + p5 + p6 + p7,
)
def objective(trial: optuna.multi_objective.trial.MultiObjectiveTrial) -> List[float]:
trial.set_user_attr("foo", "bar")
assert trial.user_attrs == {"foo": "bar"}
trial.set_user_attr("baz", "qux")
assert trial.user_attrs == {"foo": "bar", "baz": "qux"}
trial.set_user_attr("foo", "quux")
assert trial.user_attrs == {"foo": "quux", "baz": "qux"}
return [0, 0, 0]
def objective(
trial: optuna.multi_objective.trial.MultiObjectiveTrial
) -> Tuple[float, float]:
x = trial.suggest_float("x", 0, 10)
y = trial.suggest_float("y", 0, 10)
return x, y
def objective(
trial: optuna.multi_objective.trial.MultiObjectiveTrial
) -> List[float]:
trial.set_system_attr("foo", "bar")
assert trial.system_attrs == {"foo": "bar"}
return [0, 0, 0]
