def __init__(self, render, sim_config, exp_config, checkpoint_path):
import ray
from ray.tune import run_experiments
from ray.tune.registry import register_env
from ray import tune
import yaml
from SingleLaneIDM.SimulatorCode.main_env import Wrapper
from ray.rllib.agents.ppo.ppo import PPOAgent
import os
import pickle
if render == 1:
sim_config["config"]["render"] = True
else:
sim_config["config"]["render"] = False
sim_config["config"]["acc-noise"] = False
exp_name = list(exp_config.keys())[0]
exp_config[exp_name]["config"]["num_gpus"] = 0
exp_config[exp_name]["config"]["num_workers"] = 1
exp_config[exp_name]["config"]["num_envs_per_worker"] = 1
env_creator_name = "tsim-v0"
register_env(env_creator_name, lambda config: Wrapper(sim_config))
ray.init()
self.agent = PPOAgent(env="tsim-v0",
config=exp_config[exp_name]["config"])
self.agent.restore(checkpoint_path)
def __init__(self, render, sim_config, exp_config, checkpoint_path):
import ray
from ray.tune import run_experiments
from ray.tune.registry import register_env
from ray import tune
import yaml
from SingleLaneIDM.SimulatorCode.main_env import Wrapper
from ray.rllib.agents.dqn.apex import ApexAgent
import ray.rllib.agents.dqn as apex
import os
import pickle
if render == 1:
sim_config["config"]["render"] = True
else:
sim_config["config"]["render"] = False
sim_config["config"]["acc-noise"] = False
exp_name = list(exp_config.keys())[0]
exp_config[exp_name]["config"]["num_gpus"] = 0
exp_config[exp_name]["config"]["num_workers"] = 2
exp_config[exp_name]["config"]["num_envs_per_worker"] = 1
env_creator_name = "tsim-v0"
register_env(env_creator_name, lambda config: Wrapper(sim_config))
ray.init()
self.agent = ApexAgent(env="tsim-v0",
config=exp_config[exp_name]["config"])
self.agent.restore(checkpoint_path)
self.agent.optimizer.foreach_evaluator(lambda ev: ev.for_policy(
lambda pi: pi.set_epsilon(0.0), policy_id="default"))
if args.render == 1:
sim_config["config"]["render"] = True
else:
sim_config["config"]["render"] = False
sim_config["config"]["trajec-file-path"] = os.getcwd() + trajec_path
sim_config["config"]["external-controller"] = True
sim_config["config"]["test-mode"] = True
sim_config["config"]["test-file-path"] = os.getcwd() + test_trajec_path
sim_config["config"]["enable-traffic-light"] = False
exp_name = list(exp_config.keys())[0]
exp_config[exp_name]["config"]["horizon"] = int(
sim_config["config"]["horizon"])
env = Wrapper(sim_config)
controller = PPORLController(False, sim_config, exp_config,
args.checkpoint_file)
print(env.observation_space)
print(env.action_space)
episodes = args.num_episodes
horizon = args.episode_length
print(horizon)
for episode in range(0, episodes):
prev_state = env.reset(args.density)
episode_reward = 0.0
#lstm_state = [np.zeros(256), np.zeros(256)]
type=str,
help="ppo experiment configuration file")
if __name__ == "__main__":
args = parser.parse_args()
trajec_path = "/SingleLaneIDM/SimulatorCode/micro.pkl"
with open(args.sim_config_file, "r") as handle:
sim_config = yaml.load(handle)
with open(args.apex_config_file, "r") as handle:
exp_config = yaml.load(handle)
sim_config["config"]["render"] = False
sim_config["config"]["render-grid"] = False
sim_config["config"]["trajec-file-path"] = os.getcwd() + trajec_path
sim_config["config"]["external-controller"] = True
exp_name = list(exp_config.keys())[0]
exp_config[exp_name]["config"]["callbacks"]["on_episode_end"] = None
exp_config[exp_name]["config"]["horizon"] = int(
sim_config["config"]["horizon"])
env_creator_name = "tsim-v0"
register_env(env_creator_name, lambda config: Wrapper(sim_config))
#print(exp_config)
ray.init()
run_experiments(exp_config)
exp_config = yaml.load(handle)
sim_config["config"]["render"] = False
sim_config["config"]["trajec-file-path"] = os.getcwd() + trajec_path
sim_config["config"]["external-controller"] = True
sim_config["config"]["enable-traffic-light"] = True
num_episodes = args.num_episodes
episode_length = args.episode_length
exp_name = list(exp_config.keys())[0]
exp_config[exp_name]["config"]["horizon"] == int(
sim_config["config"]["horizon"])
env = Wrapper(sim_config)
controller = PPORLController(False, sim_config, exp_config,
args.checkpoint_file)
global_data_dict["num_episodes"] = num_episodes
global_data_dict["episode-length"] = episode_length
global_data_dict["time-period"] = sim_config["config"]["time-period"]
global_data_dict["data"] = {}
for density in densities:
density_data = {}
completed_episodes = 0
while completed_episodes < num_episodes: