model.py 文件源码

def forward(self, x):
        # print("aa", x)
        x = self.embed(x) # (N,W,D)
        # print("embed", x)

        if self.args.static:
            x = Variable(x.data)
        # print("var", x)

        x = x.unsqueeze(1) # (N,Ci,W,D)
        x = [F.relu(conv(x)).squeeze(3) for conv in self.convs1] #[(N,Co,W), ...]*len(Ks)
        x = [F.max_pool1d(i, i.size(2)).squeeze(2) for i in x] #[(N,Co), ...]*len(Ks)
        x = torch.cat(x, 1)
        '''
        x1 = self.conv_and_pool(x,self.conv13) #(N,Co)
        x2 = self.conv_and_pool(x,self.conv14) #(N,Co)
        x3 = self.conv_and_pool(x,self.conv15) #(N,Co)
        x = torch.cat((x1, x2, x3), 1) # (N,len(Ks)*Co)
        '''
        x = self.dropout(x) # (N,len(Ks)*Co)
        logit = self.fc1(x) # (N,C)
        return logit