import gym from ditk import logging from ding.model import VAC from ding.policy import IMPALAPolicy from ding.envs import SubprocessEnvManagerV2 from ding.data import DequeBuffer from ding.config import compile_config from ding.framework import task, ding_init from ding.framework.context import OnlineRLContext from ding.framework.middleware import OffPolicyLearner, StepCollector, interaction_evaluator, data_pusher, \ CkptSaver, online_logger, termination_checker from ding.utils import set_pkg_seed from dizoo.box2d.lunarlander.config.lunarlander_impala_config import main_config, create_config from dizoo.box2d.lunarlander.envs import LunarLanderEnv def main(): logging.getLogger().setLevel(logging.INFO) cfg = compile_config(main_config, create_cfg=create_config, auto=True) ding_init(cfg) with task.start(async_mode=False, ctx=OnlineRLContext()): collector_env = SubprocessEnvManagerV2( env_fn=[lambda: LunarLanderEnv(cfg.env) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager ) evaluator_env = SubprocessEnvManagerV2( env_fn=[lambda: LunarLanderEnv(cfg.env) for _ in range(cfg.env.evaluator_env_num)], cfg=cfg.env.manager ) set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) model = VAC(**cfg.policy.model) buffer_ = DequeBuffer( size=cfg.policy.other.replay_buffer.replay_buffer_size, sliced=cfg.policy.other.replay_buffer.sliced ) policy = IMPALAPolicy(cfg.policy, model=model) task.use(interaction_evaluator(cfg, policy.eval_mode, evaluator_env)) task.use(StepCollector(cfg, policy.collect_mode, collector_env, random_collect_size=1024)) task.use(data_pusher(cfg, buffer_, group_by_env=True)) task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) task.use(online_logger(train_show_freq=300)) task.use(CkptSaver(policy, cfg.exp_name, train_freq=10000)) task.use(termination_checker(max_env_step=2e6)) task.run() if __name__ == "__main__": main()