def __init__()

in gala/envs.py [0:0]


    def __init__(self, venv, nstack, device=None):
        self.venv = venv
        self.nstack = nstack

        wos = venv.observation_space  # wrapped ob space
        self.shape_dim0 = wos.shape[0]

        low = np.repeat(wos.low, self.nstack, axis=0)
        high = np.repeat(wos.high, self.nstack, axis=0)

        if device is None:
            device = torch.device('cpu')
        self.stacked_obs = torch.zeros((venv.num_envs, ) +
                                       low.shape).to(device)

        observation_space = gym.spaces.Box(
            low=low, high=high, dtype=venv.observation_space.dtype)
        VecEnvWrapper.__init__(self, venv, observation_space=observation_space)