def test_0_donothing(self):
agent = DoNothingAgent(self.env.helper_action_player)
i, cum_reward = self._aux_test_agent(agent)
assert i == 31, "The powerflow diverged before step 30 for do nothing"
assert np.abs(
cum_reward - 619.994619
) <= self.tol_one, "The reward has not been properly computed"
"""
Close all the environments and all the processes.
"""
for remote in self._remotes:
remote.send(('c', None))
if __name__ == "__main__":
from tqdm import tqdm
env = make()
nb_env = 8 # change that to adapt to your system
NB_STEP = 1000 # number of step for each environment
agent = DoNothingAgent(env.action_space)
multi_envs = MultiEnvironment(env=env, nb_env=nb_env)
obs = multi_envs.reset()
rews = [env.reward_range[0] for i in range(nb_env)]
dones = [False for i in range(nb_env)]
total_reward = 0.
for i in tqdm(range(NB_STEP)):
acts = [None for _ in range(nb_env)]
for env_act_id in range(nb_env):
acts[env_act_id] = agent.act(obs[env_act_id], rews[env_act_id],
dones[env_act_id])
obs, rews, dones, infos = multi_envs.step(acts)
total_reward += np.sum(rews)
len(rews)