models.py 文件源码

def forward(self, x):
        nBatch = x.size(0)

        x = self.fc1(x)

        L = self.M*self.L
        Q = L.mm(L.t()) + self.args.eps*Variable(torch.eye(self.nHidden)).cuda()
        Q = Q.unsqueeze(0).expand(nBatch, self.nHidden, self.nHidden)
        G = self.G.unsqueeze(0).expand(nBatch, self.nineq, self.nHidden)
        h = self.G.mv(self.z0)+self.s0
        h = h.unsqueeze(0).expand(nBatch, self.nineq)
        e = Variable(torch.Tensor())
        x = QPFunction()(Q, x, G, h, e, e)
        x = x[:,:self.nFeatures]

        return x