model_BiGRU.py 文件源码

def forward(self, input):
        embed = self.embed(input)
        embed = self.dropout(embed)  # add this reduce the acc
        input = embed.view(len(input), embed.size(1), -1)
        # gru
        gru_out, hidden = self.bigru(input, self.hidden)
        gru_out = torch.transpose(gru_out, 0, 1)
        gru_out = torch.transpose(gru_out, 1, 2)
        # pooling
        # gru_out = F.tanh(gru_out)
        gru_out = F.max_pool1d(gru_out, gru_out.size(2)).squeeze(2)
        gru_out = F.tanh(gru_out)
        # linear
        y = self.hidden2label(gru_out)
        logit = y
        return logit