class_docstr: An input filter is a module that filters the input from an environment to the agent.
class_docstr_tok: ["An","input","filter","is","a","module","that","filters","the","input","from","an","environment","to","the","agent","."]
docstr: Given the input reward space, returns the corresponding filtered reward space
  This function should not be updated!
  :param input_reward_space: the input reward space
  :return: the filtered reward space
code: def get_filtered_reward_space(
      self, input_reward_space: RewardSpace
  ) -> RewardSpace:
      """
      Given the input reward space, returns the corresponding filtered reward space
      This function should not be updated!
      :param input_reward_space: the input reward space
      :return: the filtered reward space
      """
      filtered_reward_space = copy.deepcopy(input_reward_space)
      for filter in self._reward_filters.values():
          filtered_reward_space = filter.get_filtered_reward_space(
              filtered_reward_space
          )
      return filtered_reward_space
  
imports: import copy
  import os
  from collections import OrderedDict
  from copy import deepcopy
  from typing import Dict, Union, List
  from rl_coach.core_types import EnvResponse, ActionInfo, Transition
  from rl_coach.spaces import ActionSpace, RewardSpace, ObservationSpace
  from rl_coach.utils import force_list
label_desc: Use image node_id 7 for calling the InputFilter obj's underlying member method code with example usage: obj.get_filtered_reward_space(input_reward_space) and returns: filtered_reward_space