class_docstr: Augments early stopping in XGBoost to also consider time_limit, memory usage, and usage of adaptive early stopping methods.
  
  Parameters
  ----------
  rounds : int or tuple
     If int, The possible number of rounds without the trend occurrence.
     If tuple, contains early stopping class as first element and class init kwargs as second element.
class_docstr_tok: ["Augments","early","stopping","in","XGBoost","to","also","consider","time_limit",",","memory","usage",",","and","usage","of","adaptive","early","stopping","methods",".","Parameters","--","--","--","--","--","rounds",":","int","or","tuple","If","int",",","The","possible","number","of","rounds","without","the","trend","occurrence",".","If","tuple",",","contains","early","stopping","class","as","first","element","and","class","init","kwargs","as","second","element","."]
code: def after_iteration(self, model, epoch, evals_log):
      should_stop = super().after_iteration(model, epoch, evals_log)
      if should_stop:
          return should_stop
      is_best_iter = self.current_rounds == 0
      should_stop = self.es.update(
          cur_round=epoch, is_best=is_best_iter
      )
      if should_stop:
          return should_stop
      if self._time_check(model=model, epoch=epoch):
          return True
      if epoch % 10 == 0 and self._memory_check(model=model):
          return True
      return should_stop
  
file_path: autogluon/tabular/src/autogluon/tabular/models/xgboost/callbacks.py
imports: import logging
  import time
  from xgboost.callback import EarlyStopping
  from autogluon.common.utils.lite import disable_if_lite_mode
  from autogluon.common.utils.resource_utils import ResourceManager
  from autogluon.core.utils.early_stopping import SimpleES
label_desc: Use image node_id 3 for calling the EarlyStoppingCustom obj's underlying member method code with example usage: obj.after_iteration(model, epoch, evals_log) and returns: should_stop, should_stop, should_stop, True, True