def random_rollout(spec, kwargs):
env = FlattenDictWrapper(spec.make(**kwargs), ['observation', 'desired_goal', 'achieved_goal'])
agent = lambda ob: env.action_space.sample()
ob = env.reset()
for _ in range(10):
assert env.observation_space.contains(ob)
a = agent(ob)
assert env.action_space.contains(a)
(ob, _reward, done, _info) = env.step(a)
if done:
break
env.close()
def environment(spec, kwargs):
env = FlattenDictWrapper(spec.make(**kwargs), ['observation', 'desired_goal', 'achieved_goal'])
ob_space = env.observation_space
act_space = env.action_space
ob = env.reset()
assert ob_space.contains(ob), 'Reset observation: {!r} not in space'.format(ob)
a = act_space.sample()
observation, reward, done, _info = env.step(a)
assert ob_space.contains(observation), 'Step observation: {!r} not in space'.format(observation)
assert np.isscalar(reward), "{} is not a scalar for {}".format(reward, env)
assert isinstance(done, bool), "Expected {} to be a boolean".format(done)
for mode in env.metadata.get('render.modes', []):
env.render(mode=mode)
# Make sure we can render the environment after close.
for mode in env.metadata.get('render.modes', []):
env.render(mode=mode)
env.close()
