class_docstr: A linear mapping of two box action spaces. For example, if the action space of the
  environment consists of continuous actions between 0 and 1, and we want the agent to choose actions between -1 and 1,
  the LinearBoxToBoxMap can be used to map the range -1 and 1 to the range 0 and 1 in a linear way. This means that the
  action -1 will be mapped to 0, the action 1 will be mapped to 1, and the rest of the actions will be linearly mapped
  between those values.
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code: def validate_output_action_space(
      self, output_action_space: BoxActionSpace
  ):
      if not isinstance(output_action_space, BoxActionSpace):
          raise ValueError(
              "BoxActionSpace discretization only works with an output space of type BoxActionSpace. "
              "The given output space is {}".format(output_action_space)
          )
  
file_path: coach/rl_coach/filters/action/linear_box_to_box_map.py
imports: from typing import Union
  import numpy
  from rl_coach.core_types import ActionType
  from rl_coach.filters.action.action_filter import ActionFilter
  from rl_coach.spaces import BoxActionSpace
label_desc: Use image node_id 2 for calling the LinearBoxToBoxMap obj's underlying member method code with example usage: obj.validate_output_action_space(output_action_space) without return types