class_docstr: Clips the reward values into a given range. For example, in DQN, the Atari rewards are
  clipped into the range -1 and 1 in order to control the scale of the returns.
code: def filter(
      self, reward: RewardType, update_internal_state: bool = True
  ) -> RewardType:
      reward = float(reward)
  
      if self.clipping_high:
          reward = min(reward, self.clipping_high)
      if self.clipping_low:
          reward = max(reward, self.clipping_low)
  
      return reward
  
file_path: coach/rl_coach/filters/reward/reward_clipping_filter.py
imports: import numpy
  from rl_coach.core_types import RewardType
  from rl_coach.filters.reward.reward_filter import RewardFilter
  from rl_coach.spaces import RewardSpace
label_desc: Use image node_id 2 for calling the RewardClippingFilter obj's underlying member method code with example usage: obj.filter(reward, update_internal_state) and returns: reward