keras/src/metrics/confusion_metrics.py/RecallAtPrecision/result
class RecallAtPrecision:    def result(self):
        recalls = ops.divide_no_nan(
            self.true_positives,
            ops.add(self.true_positives, self.false_negatives),
        )
        precisions = ops.divide_no_nan(
            self.true_positives,
            ops.add(self.true_positives, self.false_positives),
        )
        return self._find_max_under_constraint(
            precisions, recalls, ops.greater_equal
        )