code: def after_epoch(self):
      if self.best_epoch_stop is not None:
          if self.epoch >= self.best_epoch_stop:
              logger.log(
                  20,
                  f"\tStopping at the best epoch learned earlier - {self.epoch}.",
              )
              raise CancelFitException()
  
      super().after_epoch()
  
      if self.new_best:
          self.wait = 0
      else:
          loss_val = self.recorder.values[-1][self.idx]
          if np.isnan(loss_val):
              if self.epoch == 0:
                  raise AssertionError(
                      f"WARNING: NaN loss encountered in epoch {self.epoch}!"
                  )
              else:
                  logger.log(
                      30,
                      f"WARNING: NaN loss encountered in epoch {self.epoch}: early stopping",
                  )
                  raise CancelFitException()
          self.wait += 1
          if self.wait >= self.patience:
              logger.log(
                  20,
                  f"No improvement since epoch {self.epoch - self.wait}: early stopping",
              )
              raise CancelFitException()
  
      if self.time_limit:
          time_elapsed = time.time() - self.start_time
          time_left = self.time_limit - time_elapsed
          time_per_epoch = time_elapsed / (self.epoch + 1)
          if time_left < time_per_epoch:
              logger.log(
                  20,
                  f"\tRan out of time, stopping training early. (Stopping on epoch {self.epoch})",
              )
              raise CancelFitException()
  
imports: import logging
  import time
  import numpy
  from fastai.callback.core import Callback, CancelFitException
  from fastai.callback.tracker import TrackerCallback
  from fastcore.basics import store_attr
label_desc: Use image node_id 3 for calling the EarlyStoppingCallbackWithTimeLimit obj's underlying member method code with example usage: obj.after_epoch() without return types