def evaluate(
        self,
    ) -> Optional[Union[Dict[str, Any], Tuple[Dict[str, Any], TDetPredictions_co]]]:
        """
        Computes the performance metrics on the outputs previously obtained
        through `update()`.

        :return: If running in the main process, the predicted metrics. At
            least a dictionary of metric_name -> value is required. In
            addition, the evaluator may return a second value representing
            dataset/evaluator-specific additional info. If running in
            a non-main process, it should do nothing and return None.
        """
        pass

        Computes the performance metrics on the outputs previously obtained
        through `update()`.

        :return: If running in the main process, the predicted metrics. At
            least a dictionary of metric_name -> value is required. In
            addition, the evaluator may return a second value representing
            dataset/evaluator-specific additional info. If running in
            a non-main process, it should do nothing and return None.
        
avalanche/evaluation/metrics/detection.py