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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def evaluate(self, eval_iter: data_io.BaseParallelSampleIter, eval_metric: mx.metric.EvalMetric):
 """ Resets and recomputes evaluation metric on given data iterator. """

        for eval_batch in eval_iter:
            self.module.forward(eval_batch, is_train=False)
            self.module.update_metric(eval_metric, eval_batch.label)