How to use the aif360.metrics.utils.compute_num_gen_TF_PN function in aif360

optionally conditioned on protected attributes. Generalized counts are
        based on scores and not on the hard predictions.

        Args:
            privileged (bool, optional): Boolean prescribing whether to
                condition this metric on the `privileged_groups`, if `True`, or
                the `unprivileged_groups`, if `False`. Defaults to `None`
                meaning this metric is computed over the entire dataset.
        Returns:
            dict: Number of generalized true positives, generalized false
            positives, generalized true negatives, generalized false negatives
            (optionally conditioned).
        """
        condition = self._to_condition(privileged)

        return utils.compute_num_gen_TF_PN(self.dataset.protected_attributes,
            self.dataset.labels, self.classified_dataset.scores,
            self.dataset.instance_weights,
            self.dataset.protected_attribute_names,
            self.dataset.favorable_label, self.dataset.unfavorable_label,
            condition=condition)