def test_pickleable(self):
inner_env = PointEnv(goal=(1., 2.))
env = NormalizedEnv(inner_env, scale_reward=10.)
round_trip = pickle.loads(pickle.dumps(env))
assert round_trip
assert round_trip._scale_reward == env._scale_reward
assert np.array_equal(round_trip.env._goal, env.env._goal)
step_env(round_trip)
round_trip.close()
env.close()
def test_does_not_modify_action(self):
inner_env = PointEnv(goal=(1., 2.))
env = NormalizedEnv(inner_env, scale_reward=10.)
a = env.action_space.high + 1.
a_copy = a
env.reset()
env.step(a)
assert np.array_equal(a, a_copy)
env.close()
def test_pickleable(self):
inner_env = CartpoleEnv(obs_noise=5.)
env = NormalizedEnv(inner_env, scale_reward=10.)
round_trip = pickle.loads(pickle.dumps(env))
assert round_trip
assert round_trip._scale_reward == env._scale_reward
assert round_trip.env.obs_noise == env.env.obs_noise
step_env(round_trip)
def test_visualization(self):
inner_env = PointEnv(goal=(1., 2.))
env = NormalizedEnv(inner_env)
env.visualize()
env.reset()
assert inner_env.render_modes == env.render_modes
mode = inner_env.render_modes[0]
assert inner_env.render(mode) == env.render(mode)
def test_does_not_modify_action(self):
inner_env = CartpoleEnv(obs_noise=5.)
env = NormalizedEnv(inner_env, scale_reward=10.)
a = env.action_space.sample()
a_copy = a
env.reset()
env.step(a)
self.assertEquals(a, a_copy)
def test_no_flatten_obs(self):
inner_env = PointEnv(goal=(1., 2.))
env = NormalizedEnv(inner_env, flatten_obs=False)
obs = env.reset()[0]
assert obs.shape == env.observation_space.shape
def __init__(self, env):
Serializable.quick_init(self, locals())
Parameterized.__init__(self)
NormalizedEnv.__init__(self, env)