class_docstr: Interface for strategies used to stop the optimization.
  
  Note that this is different from the `BaseEarlyStoppingStrategy`,
  the functionality of which is to decide whether a trial with partial
  results available during evaluation should be stopped before
  fully completing. In global early stopping, the decision is about
  whether or not to stop the overall optimzation altogether (e.g. b/c
  the expected marginal gains of running additional evaluations do not
  justify the cost of running these trials).
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docstr: Initiating a base stopping strategy.
  
  Args:
      min_trials: Minimum number of trials before the stopping strategy kicks in.
      inactive_when_pending_trials: If set, the optimization will not stop as
          long as it has running trials.
docstr_tok: ["Initiating","a","base","stopping","strategy",".","Args",":","min_trials",":","Minimum","number","of","trials","before","the","stopping","strategy","kicks","in",".","inactive_when_pending_trials",":","If","set",",","the","optimization","will","not","stop","as","long","as","it","has","running","trials","."]
code: def __init__(
      self, min_trials: int, inactive_when_pending_trials: bool = True
  ) -> None:
      """
      Initiating a base stopping strategy.
  
      Args:
          min_trials: Minimum number of trials before the stopping strategy kicks in.
          inactive_when_pending_trials: If set, the optimization will not stop as
              long as it has running trials.
      """
      self.min_trials = min_trials
      self.inactive_when_pending_trials = inactive_when_pending_trials
  
file_path: Ax/ax/global_stopping/strategies/base.py
imports: from abc import ABC, abstractmethod
  from typing import Any, Tuple
  from ax.core.base_trial import TrialStatus
  from ax.core.experiment import Experiment
  from ax.utils.common.base import Base
label_desc: Use image node_id 1 to create a new BaseGlobalStoppingStrategy object from inherited base classes: ABC, Base with example: obj = BaseGlobalStoppingStrategy(min_trials, inactive_when_pending_trials)