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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 eval_valid(self, feval=None):
 """Evaluate for validation data. Parameters feval : callable or None, optional (default=None) Customized evaluation function. Should accept two parameters: preds, train_data, and return (eval_name, eval_result, is_higher_better) or list of such tuples. For multi-class task, the preds is group by class_id first, then group by row_id. If you want to get i-th row preds in j-th class, the access way is preds[j * num_data + i]. Returns ------- result : list List with evaluation results. """

        return [item for i in range_(1, self.__num_dataset)
                for item in self.__inner_eval(self.name_valid_sets[i - 1], i, feval)]