code: def integrate_until_event(self, t0, event_fn):
      assert (
          self.step_size is not None
      ), "Event handling for fixed step solvers currently requires `step_size` to be provided in options."
  
      t0 = t0.type_as(self.y0.abs())
      y0 = self.y0
      dt = self.step_size
  
      sign0 = torch.sign(event_fn(t0, y0))
      max_itrs = 20000
      itr = 0
      while True:
          itr += 1
          t1 = t0 + dt
          dy, f0 = self._step_func(self.func, t0, dt, t1, y0)
          y1 = y0 + dy
  
          sign1 = torch.sign(event_fn(t1, y1))
  
          if sign0 != sign1:
              if self.interp == "linear":
                  interp_fn = lambda t: self._linear_interp(
                      t0, t1, y0, y1, t
                  )
              elif self.interp == "cubic":
                  f1 = self.func(t1, y1)
                  interp_fn = lambda t: self._cubic_hermite_interp(
                      t0, y0, f0, t1, y1, f1, t
                  )
              else:
                  raise ValueError(
                      f"Unknown interpolation method {self.interp}"
                  )
              event_time, y1 = find_event(
                  interp_fn, sign0, t0, t1, event_fn, float(self.atol)
              )
              break
          else:
              t0, y0 = t1, y1
  
          if itr >= max_itrs:
              raise RuntimeError(
                  f"Reached maximum number of iterations {max_itrs}."
              )
      solution = torch.stack([self.y0, y1], dim=0)
      return event_time, solution
  
imports: import abc
  import torch
  from .event_handling import find_event
  from .misc import _handle_unused_kwargs
label_desc: Use image node_id 6 for calling the FixedGridODESolver obj's underlying member method code with example usage: obj.integrate_until_event(t0, event_fn) and returns: event_time,  solution