code: def test_odeint(self):
      for reverse in (False, True):
          for dtype in DTYPES:
              for device in DEVICES:
                  for method in METHODS:
                      # TODO: remove after event handling gets enabled.
                      if method == "scipy_solver":
                          continue
  
                      for ode in ("constant", "sine"):
                          with self.subTest(
                              reverse=reverse,
                              dtype=dtype,
                              device=device,
                              ode=ode,
                              method=method,
                          ):
                              if method == "explicit_adams":
                                  tol = 7e-2
                              elif method == "euler":
                                  tol = 5e-3
                              else:
                                  tol = 1e-4
  
                              f, y0, t_points, sol = construct_problem(
                                  dtype=dtype,
                                  device=device,
                                  ode=ode,
                                  reverse=reverse,
                              )
  
                              def event_fn(t, y):
                                  return torch.sum(y - sol[2]).real
  
                              if method in FIXED_METHODS:
                                  options = {
                                      "step_size": 0.01,
                                      "interp": "cubic",
                                  }
                              else:
                                  options = {}
  
                              t, y = torchdiffeq.odeint(
                                  f,
                                  y0,
                                  t_points[0:2],
                                  event_fn=event_fn,
                                  method=method,
                                  options=options,
                              )
                              y = y[-1]
                              self.assertLess(rel_error(sol[2], y), tol)
                              self.assertLess(
                                  rel_error(t_points[2], t), tol
                              )
  
file_path: torchdiffeq/tests/event_tests.py
imports: import unittest
  import torch
  import torchdiffeq
  from problems import construct_problem, DTYPES, DEVICES, METHODS, FIXED_METHODS
label_desc: Use image node_id 1 for calling the TestEventHandling obj's underlying member method code with example usage: obj.test_odeint() and returns: torch