Description : Print sentence for prediction result

def infer(self, input_data, input_label):
        """
        Description : Print sentence for prediction result
        """
        sum_losses = 0
        len_losses = 0
        for data, label in zip(input_data, input_label):
            pred = self.net(data)
            sum_losses += mx.nd.array(self.loss_fn(pred, label)).sum().asscalar()
            len_losses += len(data)
            pred_convert = char_beam_search(pred)
            label_convert = char_conv(label.asnumpy())
            for target, pred in zip(label_convert, pred_convert):
                print("target:{t}  pred:{p}".format(t=target, p=pred))
        return sum_losses, len_losses