sinergym.utils.wrappers.MultiObsWrapper
- class sinergym.utils.wrappers.MultiObsWrapper(env: Env, n: int = 5, flatten: bool = True)
- __init__(env: Env, n: int = 5, flatten: bool = True) None
Stack of observations.
- Parameters:
env (Env) – Original Gym environment.
n (int, optional) – Number of observations to be stacked. Defaults to 5.
flatten (bool, optional) – Whether or not flat the observation vector. Defaults to True.
Methods
__init__
(env[, n, flatten])Stack of observations.
class_name
()Returns the class name of the wrapper.
close
()Closes the wrapper and
env
.get_wrapper_attr
(name)Gets an attribute from the wrapper and lower environments if name doesn't exist in this object.
has_wrapper_attr
(name)Checks if the given attribute is within the wrapper or its environment.
render
()Uses the
render()
of theenv
that can be overwritten to change the returned data.reset
([seed, options])Resets the environment.
set_wrapper_attr
(name, value)Sets an attribute on this wrapper or lower environment if name is already defined.
step
(action)Performs the action in the new environment.
wrapper_spec
(**kwargs)Generates a WrapperSpec for the wrappers.
Attributes
action_space
Return the
Env
action_space
unless overwritten then the wrapperaction_space
is used.metadata
Returns the
Env
metadata
.np_random
Returns the
Env
np_random
attribute.np_random_seed
Returns the base environment's
np_random_seed
.observation_space
Return the
Env
observation_space
unless overwritten then the wrapperobservation_space
is used.render_mode
Returns the
Env
render_mode
.spec
Returns the
Env
spec
attribute with the WrapperSpec if the wrapper inherits from EzPickle.unwrapped
Returns the base environment of the wrapper.
- logger = <Logger WRAPPER MultiObsWrapper (INFO)>
- reset(seed: int | None = None, options: Dict[str, Any] | None = None) Tuple[ndarray, Dict[str, Any]]
Resets the environment.
- Returns:
Stacked previous observations.
- Return type:
np.ndarray
- step(action: int | ndarray) Tuple[ndarray, float, bool, bool, Dict[str, Any]]
Performs the action in the new environment.
- Parameters:
action (Union[int, np.ndarray]) – Action to be executed in environment.
- Returns:
Tuple with next observation, reward, bool for terminated episode and dict with extra information.
- Return type:
Tuple[np.ndarray, float, bool, Dict[str, Any]]