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gym_utils

GymObservable

Simple class interface for observable objects. These objects should implement a way to grab observations, (get_obs()), and should define an observation space that is created when load_observation_space() is called

Parameters:

Name Type Description Default
kwargs

dict, does nothing, used to sink any extraneous arguments during initialization

 {}
Source code in utils/gym_utils.py 
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class GymObservable(metaclass=ABCMeta):
    """
    Simple class interface for observable objects. These objects should implement a way to grab observations,
    (get_obs()), and should define an observation space that is created when load_observation_space() is called

    Args:
        kwargs: dict, does nothing, used to sink any extraneous arguments during initialization
    """
    def __init__(self, *args, **kwargs):
        # Initialize variables that we will fill in later
        self.observation_space = None

        # Call any super methods
        super().__init__(*args, **kwargs)

    @abstractmethod
    def get_obs(self, **kwargs):
        """
        Get observations for the object. Note that the shape / nested structure should match that
        of @self.observation_space!

        Args:
            kwargs (dict): Any keyword args necessary for grabbing observations

        Returns:
            OrderedDict: Keyword-mapped observations mapping observation names to nested observations
        """
        raise NotImplementedError()

    @staticmethod
    def _build_obs_box_space(shape, low, high, dtype=np.float32):
        """
        Helper function that builds individual observation box spaces.

        Args:
            shape (n-array): Shape of the space
            low (float): Lower bound of the space
            high (float): Upper bound of the space

        Returns:
            gym.spaces.Box: Generated gym box observation space
        """
        return gym.spaces.Box(low=low, high=high, shape=shape, dtype=dtype)

    @abstractmethod
    def _load_observation_space(self):
        """
        Create the observation space for this object. Should be implemented by subclass

        Returns:
            OrderedDict: Keyword-mapped observation space for this object mapping observation name to observation space
        """
        raise NotImplementedError()

    def load_observation_space(self):
        """
        Load the observation space internally, and also return this value

        Returns:
            gym.spaces.Dict: Loaded observation space for this object
        """
        # Load the observation space and convert it into a gym-compatible dictionary
        self.observation_space = gym.spaces.Dict(self._load_observation_space())
        print(f"Loaded obs space dictionary for: {self.__class__.__name__}")

        return self.observation_space

get_obs(**kwargs) abstractmethod

Get observations for the object. Note that the shape / nested structure should match that of @self.observation_space!

Parameters:

Name Type Description Default
kwargs dict

Any keyword args necessary for grabbing observations

 {}

Returns:

Name Type Description
OrderedDict

Keyword-mapped observations mapping observation names to nested observations
Source code in utils/gym_utils.py 
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@abstractmethod
def get_obs(self, **kwargs):
    """
    Get observations for the object. Note that the shape / nested structure should match that
    of @self.observation_space!

    Args:
        kwargs (dict): Any keyword args necessary for grabbing observations

    Returns:
        OrderedDict: Keyword-mapped observations mapping observation names to nested observations
    """
    raise NotImplementedError()

load_observation_space()

Load the observation space internally, and also return this value

Returns:

Type Description

gym.spaces.Dict: Loaded observation space for this object
Source code in utils/gym_utils.py 
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def load_observation_space(self):
    """
    Load the observation space internally, and also return this value

    Returns:
        gym.spaces.Dict: Loaded observation space for this object
    """
    # Load the observation space and convert it into a gym-compatible dictionary
    self.observation_space = gym.spaces.Dict(self._load_observation_space())
    print(f"Loaded obs space dictionary for: {self.__class__.__name__}")

    return self.observation_space