model_classes.py 文件源码

def forward(self, z0, mu, dg, d2g):
        nBatch, n = z0.size()

        Q = torch.cat([torch.diag(d2g[i] + 1).unsqueeze(0) 
            for i in range(nBatch)], 0).double()
        p = (dg - d2g*z0 - mu).double()
        G = self.G.unsqueeze(0).expand(nBatch, self.G.size(0), self.G.size(1))
        h = self.h.unsqueeze(0).expand(nBatch, self.h.size(0))

        out = QPFunction(verbose=False)(Q, p, G, h, self.e, self.e)
        return out