code: def test_adjoint(self):
      for device in DEVICES:
          for method in METHODS:
              with self.subTest(device=device, method=method):
                  f, y0, t_points, _ = construct_problem(device=device)
                  func = (
                      lambda y0, t_points: torchdiffeq.odeint_adjoint(
                          f, y0, t_points, method=method
                      )
                  )
                  self.assertTrue(
                      torch.autograd.gradcheck(func, (y0, t_points))
                  )
  
file_path: torchdiffeq/tests/gradient_tests.py
imports: import unittest
  import torch
  import torchdiffeq
  from problems import construct_problem, PROBLEMS, DEVICES, METHODS
label_desc: Use image node_id 2 for calling the TestGradient obj's underlying member method code with example usage: obj.test_adjoint() without return types