def objective(trial: optuna.Trial) -> float:
x = trial.suggest_float("x", -10, 10)
y = trial.suggest_float("y", -10, 10)
trial.report(x, 0)
trial.report(y, 1)
trial.set_user_attr("x", x)
trial.set_system_attr("y", y)
return f(x, y)
def f(trial: Trial) -> float:
x = trial.suggest_int("x", 1, 1)
y = trial.suggest_categorical("y", (2.5, ))
assert isinstance(y, float)
trial.set_user_attr("train_loss", 3)
trial.set_system_attr("foo", "bar")
value = x + y # 3.5
# Test reported intermediate values, although it in practice is not "intermediate".
trial.report(value, step=0)
return value
def f(trial: Trial) -> float:
trial.set_system_attr("system_message", "test")
assert trial.system_attrs["system_message"] == "test"
return 0.0
