def __init__(self, env: Env):
"""Initialize.
:param env: gym environment to wrap.
"""
ObservationWrapper.__init__(self, env)
space = env.observation_space
assert len(space) == 2, "Expected: environment state, automata states"
assert type(space[0]) == Discrete, "Env state must be discrete"
assert type(space[1]) == MultiDiscrete, "Automata states are discrete"
self.observation_space = MultiDiscrete(
(np.insert(space[1].nvec, 0, space[0].n)))
def __init__(self, env: Env):
"""Initialize.
:param env: gym environment to wrap.
"""
ObservationWrapper.__init__(self, env)
space = env.observation_space
assert len(space) == 2, "Expected: environment state, automata states"
assert type(space[0]) == Box, "Env state must be a box"
assert type(space[1]) == MultiDiscrete, "Automata states are discrete"
automata_highs = space[1].nvec.astype(np.float32)
automata_lows = np.zeros_like(automata_highs)
automata_box = Box(automata_lows, automata_highs)
self.observation_space = combine_boxes(space[0], automata_box)
def __init__(self, env):
ObservationWrapper.__init__(self, env)
self.observation_space = spaces.Box(
low=0.0, high=1.0, shape=(84, 84), dtype=np.float32)
def __init__(self, env):
ObservationWrapper.__init__(self, env)
# Important so that gym's play.py picks up the right resolution
self.observation_space = spaces.Box(low=0, high=255,
shape=(84, 84),
dtype=np.uint8)
def __init__(self, env):
ObservationWrapper.__init__(self, env)
self.frames_since_reset = None