test_autograd.py 文件源码

def test_stochastic_require_grad(self):
        # This tests a DSD function sequence (D=deterministic, S=stochastic),
        # where all functions require grad.
        x = Variable(torch.randn(2, 10), requires_grad=True)
        y = Variable(torch.randn(2, 10), requires_grad=True)
        z = torch.normal(x + 2, 2)
        o = z + y
        z.reinforce(torch.randn(2, 10))
        o.sum().backward()
        self.assertEqual(y.grad.data, torch.ones(2, 10))
        self.assertGreater(x.grad.data.abs().sum(), 0)