class_docstr: Rescales the reward by a given factor. Rescaling the rewards of the environment has been
  observed to have a large effect (negative or positive) on the behavior of the learning process.
code: def filter(
      self, reward: RewardType, update_internal_state: bool = True
  ) -> RewardType:
      reward = float(reward) * self.rescale_factor
      return reward
  
file_path: coach/rl_coach/filters/reward/reward_rescale_filter.py
imports: 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 RewardRescaleFilter obj's underlying member method code with example usage: obj.filter(reward, update_internal_state) and returns: reward