def test_issue_185_act_multidiscrete_space(self):
for env_name in self.get_list_env():
if env_name == "blank":
continue
elif env_name == "l2rpn_neurips_2020_track1":
# takes too much time
continue
elif env_name == "l2rpn_neurips_2020_track2":
# takes too much time
continue
elif env_name == "rte_case118_example":
# takes too much time
continue
elif env_name == ENV_WITH_ALARM_NAME:
# takes too much time
continue
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
with grid2op.make(env_name, test=True) as env:
gym_env = GymEnv(env)
gym_env.action_space = MultiDiscreteActSpace(gym_env.init_env.action_space)
gym_env.seed(0)
gym_env.observation_space.seed(0)
gym_env.action_space.seed(0)
obs_gym = gym_env.reset()
assert obs_gym in gym_env.observation_space, f"error for {env_name}"
act = gym_env.action_space.sample()
assert act in gym_env.action_space, f"error for {env_name}"
obs, reward, done, info = gym_env.step(act)
assert obs in gym_env.observation_space, f"error for {env_name}"
def test_issue_185(self):
for env_name in self.get_list_env():
if env_name == "blank":
continue
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
with grid2op.make(env_name, test=True) as env:
gym_env = GymEnv(env)
gym_env.seed(0)
gym_env.observation_space.seed(0)
gym_env.action_space.seed(0)
obs_gym = gym_env.reset()
assert obs_gym["a_ex"].shape[
0] == env.n_line, f"error for {env_name}"
assert obs_gym in gym_env.observation_space, f"error for {env_name}"
def test_issue_185_obs_box_space(self):
for env_name in self.get_list_env():
if env_name == "blank":
continue
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
with grid2op.make(env_name, test=True) as env:
gym_env = GymEnv(env)
gym_env.observation_space = BoxGymObsSpace(gym_env.init_env.observation_space)
gym_env.seed(0)
gym_env.observation_space.seed(0)
gym_env.action_space.seed(0)
obs_gym = gym_env.reset()
assert obs_gym in gym_env.observation_space, f"error for {env_name}"
act = gym_env.action_space.sample()
assert act in gym_env.action_space, f"error for {env_name}"
obs, reward, done, info = gym_env.step(act)
assert obs in gym_env.observation_space, f"error for {env_name}"
def test_issue_185_act_discrete_space(self):
env_with_alarm = os.path.join(PATH_DATA_TEST,
"l2rpn_neurips_2020_track1_with_alert")
for env_name in self.get_list_env():
if env_name == "blank":
continue
elif env_name == "l2rpn_neurips_2020_track1":
# takes too much time
continue
elif env_name == "l2rpn_neurips_2020_track2":
# takes too much time
continue
elif env_name == "rte_case118_example":
# takes too much time
continue
elif env_name == env_with_alarm:
# takes too much time
continue
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
with grid2op.make(env_name, test=True) as env:
gym_env = GymEnv(env)
gym_env.action_space = DiscreteActSpace(
gym_env.init_env.action_space)
gym_env.seed(0)
gym_env.observation_space.seed(0)
gym_env.action_space.seed(0)
obs_gym = gym_env.reset()
assert obs_gym in gym_env.observation_space, f"error for {env_name}"
act = gym_env.action_space.sample()
assert act in gym_env.action_space, f"error for {env_name}"
obs, reward, done, info = gym_env.step(act)
if obs not in gym_env.observation_space:
for k in obs:
if not obs[k] in gym_env.observation_space[k]:
import pdb
pdb.set_trace()
raise RuntimeError(
f"Error for key {k} for env {env_name}")