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

                If trial is being used for multi-objective optimization.
        

        if len(self.study.directions) > 1:
            raise NotImplementedError(
                "Trial.report is not supported for multi-objective optimization."
            )

        try:
            // For convenience, we allow users to report a value that can be cast to `float`.
            value = float(value)
        except (TypeError, ValueError):
            message = "The `value` argument is of type "{}" but supposed to be a float.".format(
                type(value).__name__
            )
            raise TypeError(message) from None

        if step < 0:
            raise ValueError("The `step` argument is {} but cannot be negative.".format(step))

        intermediate_values = self.storage.get_trial(self._trial_id).intermediate_values

        if step in intermediate_values:
            // Do nothing if already reported.
            // TODO(hvy): Consider raising a warning or an error.

Instances