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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 as_list(self, label=1, **kwargs):
 """Returns the explanation as a list. Args: label: desired label. If you ask for a label for which an explanation wasn't computed, will throw an exception. Will be ignored for regression explanations. kwargs: keyword arguments, passed to domain_mapper Returns: list of tuples (representation, weight), where representation is given by domain_mapper. Weight is a float. """

        label_to_use = label if self.mode == "classification" else self.dummy_label
        ans = self.domain_mapper.map_exp_ids(self.local_exp[label_to_use], **kwargs)
        ans = [(x[0], float(x[1])) for x in ans]
        return ans