ja_lstm_tagger.py 文件源码

def predict(self, xs):
        """
        batch: list of splitted sentences
        """
        xs = [self.extractor.process(x) for x in xs]
        batchsize = len(xs)
        ws, cs, ls = zip(*xs)
        ws = map(self.emb_word, ws)
        cs = [F.squeeze(
            F.max_pooling_2d(
                self.conv_char(
                    F.expand_dims(
                        self.emb_char(c), 1)), (l, 1)))
                    for c, l in zip(cs, ls)]
        xs_f = [F.dropout(F.concat([w, c]),
            self.dropout_ratio, train=self.train) for w, c in zip(ws, cs)]
        xs_b = [x[::-1] for x in xs_f]
        cx_f, hx_f, cx_b, hx_b = self._init_state(batchsize)
        _, _, hs_f = self.lstm_f(hx_f, cx_f, xs_f, train=self.train)
        _, _, hs_b = self.lstm_b(hx_b, cx_b, xs_b, train=self.train)
        hs_b = [x[::-1] for x in hs_b]
        ys = [self.linear2(F.relu(self.linear1(F.concat([h_f, h_b]))))
                    for h_f, h_b in zip(hs_f, hs_b)]
        return [y.data[1:-1] for y in ys]