def result(self) -> Dict[int, float]:
        """
        Retrieves the running AMCA for each task.

        Calling this method will not change the internal state of the metric.

        :return: A dictionary `{task_id -> amca}`. The
            running AMCA of each task is a float value between 0 and 1.
        """
        curr_task_acc = self._get_curr_task_acc()

        all_task_ids = set(self._prev_exps_accuracies.keys())
        all_task_ids = all_task_ids.union(curr_task_acc.keys())

        mean_accs = OrderedDict()
        for task_id in sorted(all_task_ids):
            prev_accs = self._prev_exps_accuracies.get(task_id, list())
            curr_acc = curr_task_acc.get(task_id, 0)
            mean_accs[task_id] = fmean(prev_accs + [curr_acc])

        return mean_accs

        Retrieves the running AMCA for each task.

        Calling this method will not change the internal state of the metric.

        :return: A dictionary `{task_id -> amca}`. The
            running AMCA of each task is a float value between 0 and 1.
        
avalanche/evaluation/metrics/amca.py