Concatenating Observation Space with Action Space in wrappers.py Causing Error Due to Different Dimensionality

[PROMOTION01]

I'm encountering an error while running train.py, and it seems to originate from wrappers.py. Here is the error message I'm receiving:

File "D:\venv\ml_env\lib\site-packages\rl_zoo3\wrappers.py", line 150, in __init__
    low = np.concatenate((low_obs, low_action))
ValueError: all the input arrays must have the same number of dimensions, but the array at index 0 has 3 dimension(s) and the array at index 1 has 1 dimension(s)

Upon inspecting the code, it appears that the issue stems from trying to concatenate the observation space and action space, which have different dimensions.

Could anyone provide an explanation or solution for this issue?

Code
`class HistoryWrapper(gym.Wrapper[np.ndarray, np.ndarray, np.ndarray, np.ndarray]):
"""
Stack past observations and actions to give a history to the agent.

:param env:
:param horizon: Number of steps to keep in the history.
"""

def __init__(self, env: gym.Env, horizon: int = 2):
    assert isinstance(env.observation_space, spaces.Box)
    assert isinstance(env.action_space, spaces.Box)

    wrapped_obs_space = env.observation_space
    wrapped_action_space = env.action_space

    low_obs = np.tile(wrapped_obs_space.low, horizon)
    high_obs = np.tile(wrapped_obs_space.high, horizon)

    low_action = np.tile(wrapped_action_space.low, horizon)
    high_action = np.tile(wrapped_action_space.high, horizon)

    low = np.concatenate((low_obs, low_action))
    high = np.concatenate((high_obs, high_action))

    # Overwrite the observation space
    env.observation_space = spaces.Box(low=low, high=high, dtype=wrapped_obs_space.dtype)  # type: ignore[arg-type]

`