task_net.py 文件源码

def __init__(self, params, eps=1e-2):
        super(SolveNewsvendor, self).__init__()
        k = len(params['d'])
        self.Q = Variable(torch.diag(torch.Tensor(
            [params['c_quad']] + [params['b_quad']]*k + [params['h_quad']]*k)) \
                .cuda())
        self.p = Variable(torch.Tensor(
            [params['c_lin']] + [params['b_lin']]*k + [params['h_lin']]*k) \
                .cuda())
        self.G = Variable(torch.cat([
            torch.cat([-torch.ones(k,1), -torch.eye(k), torch.zeros(k,k)], 1),
            torch.cat([torch.ones(k,1), torch.zeros(k,k), -torch.eye(k)], 1),
            -torch.eye(1 + 2*k)], 0).cuda())
        self.h = Variable(torch.Tensor(
            np.concatenate([-params['d'], params['d'], np.zeros(1+ 2*k)])).cuda())
        self.one = Variable(torch.Tensor([1])).cuda()
        self.eps_eye = eps * Variable(torch.eye(1 + 2*k).cuda()).unsqueeze(0)