def __init__(self, env, horizon):
"""
Parameters
----------
horizon: int
"""
Wrapper.__init__(self, env)
self.horizon = horizon
assert self.horizon >= 1
self.current_step = 0
def test_double_wrapper_copy_reseeding(ModelClass):
seeding.set_global_seed(123)
env = Wrapper(Wrapper(ModelClass()))
c_env = deepcopy(env)
c_env.reseed()
if deepcopy(env).is_online():
traj1 = get_env_trajectory(env, 500)
traj2 = get_env_trajectory(c_env, 500)
assert not compare_trajectories(traj1, traj2)
def test_wrapper():
env = GridWorld()
wrapped = Wrapper(env)
assert isinstance(wrapped, Model)
assert wrapped.is_online()
assert wrapped.is_generative()
# calling some functions
wrapped.reset()
wrapped.step(wrapped.action_space.sample())
wrapped.sample(wrapped.observation_space.sample(),
wrapped.action_space.sample())
def test_gym_wrapper():
gym_env = gym.make('Acrobot-v1')
wrapped = Wrapper(gym_env)
assert isinstance(wrapped, Model)
assert wrapped.is_online()
assert not wrapped.is_generative()
wrapped.reseed()
# calling some gym functions
wrapped.close()
wrapped.seed()
def test_gym_copy_reseeding_2():
seeding.set_global_seed(123)
if _GYM_INSTALLED:
gym_env = gym.make('Acrobot-v1')
# nested wrapping
env = RescaleRewardWrapper(Wrapper(Wrapper(gym_env)), (0, 1))
c_env = deepcopy(env)
c_env.reseed()
if deepcopy(env).is_online():
traj1 = get_env_trajectory(env, 500)
traj2 = get_env_trajectory(c_env, 500)
assert not compare_trajectories(traj1, traj2)
def test_wrapper_seeding(ModelClass):
seeding.set_global_seed(123)
env1 = Wrapper(ModelClass())
seeding.set_global_seed(456)
env2 = Wrapper(ModelClass())
seeding.set_global_seed(123)
env3 = Wrapper(ModelClass())
if deepcopy(env1).is_online():
traj1 = get_env_trajectory(env1, 500)
traj2 = get_env_trajectory(env2, 500)
traj3 = get_env_trajectory(env3, 500)
assert not compare_trajectories(traj1, traj2)
assert compare_trajectories(traj1, traj3)
def test_gym_copy_reseeding():
seeding.set_global_seed(123)
if _GYM_INSTALLED:
gym_env = gym.make('Acrobot-v1')
env = Wrapper(gym_env)
c_env = deepcopy(env)
c_env.reseed()
if deepcopy(env).is_online():
traj1 = get_env_trajectory(env, 500)
traj2 = get_env_trajectory(c_env, 500)
assert not compare_trajectories(traj1, traj2)
def gym_make(env_name):
"""
Same as gym.make, but wraps the environment
to ensure unified seeding with rlberry.
"""
return Wrapper(gym.make(env_name))
def __init__(self, env, reward_range):
Wrapper.__init__(self, env)
self.reward_range = reward_range
assert reward_range[0] < reward_range[1]
assert reward_range[0] > -np.inf and reward_range[1] < np.inf