OpenAI Gym RLLib AssertionError in CustomEnviorment

Question

I have a custom enviorment:

class PlacementEnv(gym.Env)

    def __init__(self, sb, bb):
        self.reward = None
        self.smallBoxes = sb
        self.bigBoxes = bb

        # Define the observation space

        i = 1
        space_to_observe = {}

        for smallbox in self.smallBoxes:
            highx = smallbox.pointMax_X
            highy = smallbox.pointMax_Y
            space_single_smallbox = {
                'points_smallbox' + str(i): gym.spaces.Box(low=np.array([0, 0]), high=np.array([highx, highy]),
                                                            shape=(2,), dtype=int),
                'bbID_smallbox' + str(i): gym.spaces.Discrete(len(self.bigBoxes))}
            space_to_observe = space_to_observe | space_single_smallbox
            i = i+1

        dict_space = gym.spaces.Dict(space_to_observe)
        self.observation_space = dict_space

        # Define action space
        self.action_space = spaces.Tuple((
            spaces.Discrete(len(self.bigBoxes)),
            spaces.Box(low=0, high=3000, shape=(2,), dtype=int), 
            spaces.Discrete(8))
        ))

    def reset(self):
        i = 0
        space_to_observe = {}

        for smallbox in self.smallBoxes:
            smallbox.bb_id = None
            smallbox.insertion_point = (0, 0)
            smallbox.rotation_angle = 0
            highx = smallbox.pointMax_X
            highy = smallbox.pointMax_Y
            space_single_smallbox = {
                'points_smallbox' + str(i): gym.spaces.Box(low=np.array([0, 0]), high=np.array([highx, highy]),
                                                            shape=(2,), dtype=int),
                'bbID_smallbox' + str(i): gym.spaces.Discrete(len(self.bigBoxes))}
            space_to_observe = space_to_observe | space_single_smallbox
            i = i+1
        dict_space = gym.spaces.Dict(space_to_observe)
        self.observation_space = dict_space
        return self.observation_space

When I run the code I get the following error:

AssertionError: ERROR: `elem` (Box(0, 2, (2,), int16)) must be np.array, float or int!

I don't understand why this error comes up. I cannot see any clear hint.

Info: for everyone this code seems familiar to. This is from my post yesterday which I have deleted now as I made a couple of progress (I think :-) )

I am absolute beginner to Python and OpenAI Gym. This is my first project.

Thanks for any helpful reply. Edit: Sorry, everytime I want to start with "Hi" or "Hi guys" it is cutoff when I post the question. Don't want to be not polite! :) I searched the internet without success

Answer 1

The problem is that reset should return the initial observation from the environment--not the observation space itself. So you should either return a valid observation informed by your problem or you could do something like return self.observation_space.sample()