test_autograd.py 文件源码

def _test_backward(self):
        v_t = torch.randn(5, 5)
        x_t = torch.randn(5, 5)
        y_t = torch.rand(5, 5) + 0.1
        z_t = torch.randn(5, 5)
        grad_output = torch.randn(5, 5)
        v = Variable(v_t, requires_grad=True)
        x = Variable(x_t, requires_grad=True)
        y = Variable(y_t, requires_grad=True)
        z = Variable(z_t, requires_grad=True)

        v.backward(grad_output)
        self.assertEqual(v.grad.data, grad_output)

        a = x + (y * z) + 4 * z ** 2 * x / y
        a.backward(grad_output)
        x_grad = 4 * z_t.pow(2) / y_t + 1
        y_grad = z_t - 4 * x_t * z_t.pow(2) / y_t.pow(2)
        z_grad = 8 * x_t * z_t / y_t + y_t
        self.assertEqual(x.grad.data, x_grad * grad_output)
        self.assertEqual(y.grad.data, y_grad * grad_output)
        self.assertEqual(z.grad.data, z_grad * grad_output)