code: def test_odeint_perturb(self):
      for adjoint in (False, True):
          for dtype in DTYPES:
              for device in DEVICES:
                  for method in FIXED_METHODS:
                      for perturb in (True, False):
                          with self.subTest(
                              adjoint=adjoint,
                              dtype=dtype,
                              device=device,
                              method=method,
                              perturb=perturb,
                          ):
                              x0 = torch.tensor(
                                  [1.0, 2.0],
                                  device=device,
                                  dtype=dtype,
                                  requires_grad=True,
                              )
                              t = torch.tensor(
                                  [0.0, 1.0], device=device
                              )
                              ts = []
  
                              def f(t, x):
                                  ts.append(t.item())
                                  return -x
  
                              options = dict(
                                  step_size=0.5, perturb=perturb
                              )
  
                              with warnings.catch_warnings():
                                  odeint = (
                                      partial(
                                          torchdiffeq.odeint_adjoint,
                                          adjoint_params=(),
                                      )
                                      if adjoint
                                      else torchdiffeq.odeint
                                  )
                                  xs = odeint(
                                      f,
                                      x0,
                                      t,
                                      method=method,
                                      options=options,
                                  )
  
                              if perturb:
                                  self.assertNotIn(0.0, ts)
                                  self.assertNotIn(0.5, ts)
                              else:
                                  self.assertIn(0.0, ts)
                                  self.assertIn(0.5, ts)
  
                              if adjoint:
                                  ts.clear()
                                  with warnings.catch_warnings():
                                      xs.sum().backward()
                                  if perturb:
                                      self.assertNotIn(1.0, ts)
                                      self.assertNotIn(0.5, ts)
                                  else:
                                      self.assertIn(1.0, ts)
                                      self.assertIn(0.5, ts)
  
imports: from functools import partial
  import unittest
  import warnings
  import torch
  import torchdiffeq
  from problems import construct_problem, PROBLEMS, DTYPES, DEVICES, METHODS, ADAPTIVE_METHODS, FIXED_METHODS, SCIPY_METHODS
label_desc: Use image node_id 2 for calling the TestDiscontinuities obj's underlying member method code with example usage: obj.test_odeint_perturb() and returns: unknown