code: def test_forward(self):
      for dtype in DTYPES:
          eps = EPS[dtype]
          for device in DEVICES:
              f, y0, t_points, sol = construct_problem(
                  dtype=dtype, device=device
              )
              tuple_f = lambda t, y: (f(t, y[0]), f(t, y[1]))
              tuple_y0 = (y0, y0)
              for method in ADAPTIVE_METHODS:
                  with self.subTest(
                      dtype=dtype, device=device, method=method
                  ):
                      tuple_y = torchdiffeq.odeint(
                          tuple_f, tuple_y0, t_points, method=method
                      )
                      max_error0 = (sol - tuple_y[0]).abs().max()
                      max_error1 = (sol - tuple_y[1]).abs().max()
                      self.assertLess(max_error0, eps)
                      self.assertLess(max_error1, eps)
  
imports: import unittest
  import torch
  import torchdiffeq
  from problems import construct_problem, DTYPES, DEVICES, ADAPTIVE_METHODS
label_desc: Use image node_id 1 for calling the TestCollectionState obj's underlying member method code with example usage: obj.test_forward() without return types