Space sort

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Air Force Research Laboratory (AFRL) Autonomous Capabilities Team (ACT3) Reinforcement Learning (RL) Core.

This is a US Government Work not subject to copyright protection in the US.

The use, dissemination or disclosure of data in this file is subject to limitation or restriction. See accompanying README and LICENSE for details.

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gym_space_sort(space)

Space

Any gym.spaces.Space (or nested hierarchy of spaces) to be sorted. This sorts any gym.space.Dict in the hierarchy in KEY order. This is necessary as a workaround to a bug in ray/rllib which causes the action space that is generated from a dictionary to be in KEY order (the result of this line: https://github.com/ray-project/ray/blob/9c26d6c6de3016eb7409db8eca51f8cac4b2944e/rllib/utils/exploration/random.py#L119 which uses https://tree.readthedocs.io/en/latest/api.html#tree.map_structure, which internally uses https://tree.readthedocs.io/en/latest/api.html#tree.flatten which, per the docs, causes the returned map to be in KEY order).

Source code in corl/environment/utils/space_sort.py

def gym_space_sort(space: gym.spaces.Space):
    """
    space:
        Any gym.spaces.Space (or nested hierarchy of spaces) to be sorted. This sorts any gym.space.Dict in the hierarchy in KEY order.
        This is necessary as a workaround to a bug in ray/rllib which causes the action space that is generated from a dictionary to be
        in KEY order (the result of this line:
        https://github.com/ray-project/ray/blob/9c26d6c6de3016eb7409db8eca51f8cac4b2944e/rllib/utils/exploration/random.py#L119
        which uses https://tree.readthedocs.io/en/latest/api.html#tree.map_structure, which internally uses
        https://tree.readthedocs.io/en/latest/api.html#tree.flatten which, per the docs, causes the returned map to be in KEY order).
    """
    if isinstance(space, gym.spaces.Dict):
        space_dict: gym.spaces.Dict = typing.cast(gym.spaces.Dict, space)
        for key in space_dict.spaces:
            sub_space = space_dict.spaces[key]
            gym_space_sort(sub_space)
        space.spaces = OrderedDict(sorted(space_dict.spaces.items()))
    if isinstance(space, gym.spaces.Tuple):
        space_tuple: gym.spaces.Tuple = typing.cast(gym.spaces.Tuple, space)
        for sub_space in space_tuple.spaces:
            gym_space_sort(sub_space)