Closed xKDHx closed 1 year ago
For now you can use optuna.visualization
by passing the original study
like so:
import optuna
import optuna_distributed
def objective(trial):
# Binh and Korn function.
x = trial.suggest_float("x", 0, 5)
y = trial.suggest_float("y", 0, 3)
v0 = 4 * x**2 + 4 * y**2
v1 = (x - 5) ** 2 + (y - 5) ** 2
return v0, v1
study = optuna_distributed.from_study(
optuna.create_study(directions=["minimize", "minimize"])
)
study.optimize(objective, n_trials=100)
optuna.visualization.plot_pareto_front(study._study).show()
It's a bit hacky to access a private field of DistributedStudy
though, so I'll try to support it properly soon.
Thanks, that's an easy work around. Great work on the project btw, I've been using it for a few weeks now and all running smoothly :)
Any plans to add optuna.visualization plotting support?