def __init__(self, env, width=84, height=84, grayscale=True, dict_space_key=None):
    '\n        Warp frames to 84x84 as done in the Nature paper and later work.\n        If the environment uses dictionary observations, `dict_space_key` can be specified which indicates which\n        observation should be warped.\n        '
    super().__init__(env)
    self._width = width
    self._height = height
    self._grayscale = grayscale
    self._key = dict_space_key
    if self._grayscale:
        num_colors = 1
    else:
        num_colors = 3
    new_space = gym.spaces.Box(low=0, high=255, shape=(self._height, self._width, num_colors), dtype=np.uint8)
    if (self._key is None):
        original_space = self.observation_space
        self.observation_space = new_space
    else:
        original_space = self.observation_space.spaces[self._key]
        self.observation_space.spaces[self._key] = new_space
    assert ((original_space.dtype == np.uint8) and (len(original_space.shape) == 3))
Warp frames to 84x84 as done in the Nature paper and later work.
If the environment uses dictionary observations, `dict_space_key` can be specified which indicates which
observation should be warped.
def __init__(self, env, width=84, height=84, grayscale=True, dict_space_key=None):
    '\n        Warp frames to 84x84 as done in the Nature paper and later work.\n        If the environment uses dictionary observations, `dict_space_key` can be specified which indicates which\n        observation should be warped.\n        '
    super().__init__(env)
    self._width = width
    self._height = height
    self._grayscale = grayscale
    self._key = dict_space_key
    if self._grayscale:
        num_colors = 1
    else:
        num_colors = 3
    new_space = gym.spaces.Box(low=0, high=255, shape=(self._height, self._width, num_colors), dtype=np.uint8)
    if (self._key is None):
        original_space = self.observation_space
        self.observation_space = new_space
    else:
        original_space = self.observation_space.spaces[self._key]
        self.observation_space.spaces[self._key] = new_space
    assert ((original_space.dtype == np.uint8) and (len(original_space.shape) == 3))