def update_metric(self, eval_metric, labels, pre_sliced=False):
        """Evaluates and accumulates evaluation metric on outputs of the last forward computation.

        Parameters
        ----------
        eval_metric : EvalMetric
        labels : list of NDArray
            Typically ``data_batch.label``.
        """
        assert self.binded and self.params_initialized

        for meta, module in zip(self._metas, self._modules):
            if SequentialModule.META_TAKE_LABELS in meta and \
                    meta[SequentialModule.META_TAKE_LABELS]:
                module.update_metric(eval_metric, labels, pre_sliced)
Evaluates and accumulates evaluation metric on outputs of the last forward computation.

        Parameters
        ----------
        eval_metric : EvalMetric
        labels : list of NDArray
            Typically ``data_batch.label``.