def test_flatten(self):
env = TheanoEnv(
normalize(gym.make('Pendulum-v0'),
normalize_reward=True,
normalize_obs=True,
flatten_obs=True))
for i in range(10):
env.reset()
for e in range(5):
env.render()
action = env.action_space.sample()
next_obs, reward, done, info = env.step(action)
assert next_obs.shape == env.observation_space.low.shape
if done:
break
env.close()
def test_unflatten(self):
env = TheanoEnv(
normalize(gym.make('Blackjack-v0'),
normalize_reward=True,
normalize_obs=True,
flatten_obs=False))
for i in range(10):
env.reset()
for e in range(5):
action = env.action_space.sample()
next_obs, reward, done, info = env.step(action)
assert (env.observation_space.flatten(next_obs).shape ==
env.observation_space.flat_dim) # yapf: disable
if done:
break
env.close()
