code: def evaluate(self, eval_iter: data_io.BaseParallelSampleIter, eval_metric: mx.metric.EvalMetric):
          
          for eval_batch in eval_iter:
              self.module.forward(eval_batch, is_train=False)
              self.module.update_metric(eval_metric, eval_batch.label)
docs: Resets and recomputes evaluation metric on given data iterator.