Method test_gradient

tests/api_tests.py:28–39

(self)

                        self.assertLess(max_error1, eps)

    def test_gradient(self):
        for device in DEVICES:
            f, y0, t_points, sol = construct_problem(device=device)
            tuple_f = lambda t, y: (f(t, y[0]), f(t, y[1]))
            for method in ADAPTIVE_METHODS:
                if method == "scipy_solver":
                    continue

                with self.subTest(device=device, method=method):
                    for i in range(2):
                        func = lambda y0, t_points: torchdiffeq.odeint(tuple_f, (y0, y0), t_points, method=method)[i]
                        self.assertTrue(torch.autograd.gradcheck(func, (y0, t_points)))


if __name__ == '__main__':