code: def update_metric(self, eval_metric, labels, pre_sliced=False):
          
          self._exec_group.update_metric(eval_metric, labels, pre_sliced)
docs: Evaluates and accumulates evaluation metric on outputs of the last forward computation.
  
          See Also
          ----------
          :meth:`BaseModule.update_metric`.
  
          Parameters
          ----------
          eval_metric : EvalMetric
              Evaluation metric to use.
          labels : list of NDArray if `pre_sliced` parameter is set to `False`,
              list of lists of NDArray otherwise. Typically `data_batch.label`.
          pre_sliced: bool
              Whether the labels are already sliced per device (default: False).