from copy import deepcopy
from ditk import logging
from ding.model import DQN
from ding.policy import DQNPolicy
from ding.envs import DingEnvWrapper, SubprocessEnvManagerV2
from ding.data import DequeBuffer
from ding.config import compile_config
from ding.torch_utils import DataParallel
from ding.framework import task
from ding.framework.context import OnlineRLContext
from ding.framework.middleware import OffPolicyLearner, StepCollector, interaction_evaluator, data_pusher, \
    eps_greedy_handler, CkptSaver, nstep_reward_enhancer, termination_checker
from ding.utils import set_pkg_seed
from dizoo.atari.envs.atari_env import AtariEnv
from dizoo.atari.config.serial.pong.pong_dqn_config import main_config, create_config


def main():
    logging.getLogger().setLevel(logging.INFO)
    main_config.exp_name = 'pong_dqn_seed0_dp'
    cfg = compile_config(main_config, create_cfg=create_config, auto=True)
    with task.start(async_mode=False, ctx=OnlineRLContext()):
        collector_cfg = deepcopy(cfg.env)
        collector_cfg.is_train = True
        evaluator_cfg = deepcopy(cfg.env)
        evaluator_cfg.is_train = False
        collector_env = SubprocessEnvManagerV2(
            env_fn=[lambda: AtariEnv(collector_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager
        )
        evaluator_env = SubprocessEnvManagerV2(
            env_fn=[lambda: AtariEnv(evaluator_cfg) for _ in range(cfg.env.evaluator_env_num)], cfg=cfg.env.manager
        )

        set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda)

        model = DQN(**cfg.policy.model)
        model = DataParallel(model)
        buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size)
        policy = DQNPolicy(cfg.policy, model=model)

        task.use(interaction_evaluator(cfg, policy.eval_mode, evaluator_env))
        task.use(eps_greedy_handler(cfg))
        task.use(StepCollector(cfg, policy.collect_mode, collector_env))
        task.use(nstep_reward_enhancer(cfg))
        task.use(data_pusher(cfg, buffer_))
        task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_))
        task.use(CkptSaver(policy, cfg.exp_name, train_freq=1000))
        task.use(termination_checker(max_env_step=int(1e7)))
        task.run()


if __name__ == "__main__":
    main()