4cb81c0b6fcc39be3d782d81cb0ff776f31cc6b2,optuna/trial/_trial.py,Trial,report,#Trial#Any#Any#,507

Before Change

                If trial is being used for multi-objective optimization.
        

        return self.study.report(self, value=value, step=step)

    def should_prune(self) -> bool:
        Suggest whether the trial should be pruned or not.

After Change

            // Do nothing if already reported.
            // TODO(hvy): Consider raising a warning or an error.
            // See https://github.com/optuna/optuna/issues/852.
            return

        self.storage.set_trial_intermediate_value(self._trial_id, step, value)

    def should_prune(self) -> bool:

Instances