test_inference.py 文件源码

def setUp(self):
        # lognormal-normal model
        # putting some of the parameters inside of a torch module to
        # make sure that that functionality is ok (XXX: do this somewhere else in the future)
        self.mu0 = Variable(torch.Tensor([1.0]))  # normal prior hyperparameter
        # normal prior hyperparameter
        self.tau0 = Variable(torch.Tensor([1.0]))
        # known precision for observation likelihood
        self.tau = Variable(torch.Tensor([2.5]))
        self.n_data = 2
        self.data = Variable(torch.Tensor([[1.5], [2.2]]))  # two observations
        self.tau_n = self.tau0 + \
            Variable(torch.Tensor([self.n_data])) * self.tau  # posterior tau
        mu_numerator = self.mu0 * self.tau0 + \
            self.tau * torch.sum(torch.log(self.data))
        self.mu_n = mu_numerator / self.tau_n  # posterior mu
        self.log_mu_n = torch.log(self.mu_n)
        self.log_tau_n = torch.log(self.tau_n)