def _thunk(): env = make_env.make_env(env_id) env.seed(seed + rank) env = bench.Monitor(env, logger.get_dir() and os.path.join(logger.get_dir(), str(rank)), allow_early_resets=True) gym.logger.setLevel(logging.WARN) return env
def _thunk(): env = make_env.make_env(env_id, max_episode_len=max_episode_len) env.discrete_action_input = True env.seed(seed + rank) env = bench.Monitor(env, logger.get_dir() and os.path.join(logger.get_dir(), str(rank)), allow_early_resets=True) gym.logger.setLevel(logging.WARN) return env
def train(logdir, env_id, lr, num_timesteps, seed, timesteps_per_batch, cont=False): from sandbox.ppo_sgd import mlp_policy from sandbox.ppo_sgd import pposgd_simple from rl import logger from rl.common import set_global_seeds, tf_util as U from rl import bench from gym.envs.registration import register import multiagent import make_env logger.configure(logdir, format_strs=['log', 'json', 'tensorboard']) U.make_session(num_cpu=1).__enter__() set_global_seeds(seed) env = make_env.make_env(env_id) def policy_fn(name, ob_space, ac_space, id): pi = mlp_policy.MlpPolicy(name=name, ob_space=ob_space, ac_space=ac_space, hid_size=64, num_hid_layers=2, id=id) return pi env = bench.Monitor( env, logger.get_dir() and osp.join(logger.get_dir(), "monitor.json")) env.seed(seed) gym.logger.setLevel(logging.WARN) pposgd_simple.learn(env, policy_fn, max_timesteps=num_timesteps, timesteps_per_batch=timesteps_per_batch, clip_param=0.2, entcoeff=0.0, optim_epochs=10, optim_stepsize=lr, optim_batchsize=64, gamma=0.99, lam=0.95, schedule='linear', cont=cont) env.close() return None
def _make_env(): env = gym.make(env_id) env = MAWrapper(env) env = bench.Monitor(env, logger.get_dir()) return env
def _make_env(): env = make_env(env_id) # gym.make(env_id) env = bench.Monitor(env, logger.get_dir()) return env
def create_env(): env = make_env.make_env('simple_spread') env.seed(3) env = bench.Monitor(env, '/tmp/', allow_early_resets=True) set_global_seeds(3) return env
def _make_env(rank): env = gym.make('RoboSumo-Ant-vs-Ant-v0') env = bench.Monitor(env, logger.get_dir() and os.path.join(logger.get_dir(), str(rank))) return env