docstr: Run off-policy evaluation estimators to evaluate the trained policy performance against a dataset.
  Should only be implemented for off-policy RL algorithms.
  
  :return: None
docstr_tok: ["Run","off-policy","evaluation","estimators","to","evaluate","the","trained","policy","performance","against","a","dataset",".","Should","only","be","implemented","for","off-policy","RL","algorithms",".",":","return",":","None"]
code: def run_off_policy_evaluation(self) -> None:
      """
      Run off-policy evaluation estimators to evaluate the trained policy performance against a dataset.
      Should only be implemented for off-policy RL algorithms.
  
      :return: None
      """
      raise NotImplementedError("")
  
imports: from typing import Union, List, Dict
  import numpy
  from rl_coach.core_types import EnvResponse, ActionInfo, RunPhase, PredictionType, ActionType, Transition
  from rl_coach.saver import SaverCollection
label_desc: Use image node_id 15 for calling the AgentInterface obj's underlying member method code with example usage: obj.run_off_policy_evaluation() without return types