lstm_tagger_ph.py 文件源码

def forward(self, ws, ss, ps):
        batchsize, length = ws.shape
        xp = chainer.cuda.get_array_module(ws[0])
        ws = self.emb_word(ws) # (batch, length, word_dim)
        ss = F.reshape(self.emb_suf(ss), (batchsize, length, -1))
        ps = F.reshape(self.emb_prf(ps), (batchsize, length, -1))
        hs = F.transpose(F.concat([ws, ss, ps], 2), (1, 0, 2))
        hs = F.dropout(hs, self.dropout_ratio, train=self.train)
        hs = F.split_axis(hs, length, 0)
        hs_f = []
        hs_b = []
        self._init_state()
        for h_in_f, h_in_b in zip(hs, reversed(hs)):
            h_f = self.lstm_f2(self.lstm_f1(F.squeeze(h_in_f, 0)))
            hs_f.append(h_f)
            h_b = self.lstm_b2(self.lstm_b1(F.squeeze(h_in_b, 0)))
            hs_b.append(h_b)

        ys = [self.linear2(F.relu(self.linear1(F.concat([h_f, h_b]))))
                for h_f, h_b in zip(hs_f, reversed(hs_b))]
        return ys