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from copy import deepcopy |
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from ditk import logging |
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from ding.model import DQN |
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from ding.policy import DQNPolicy |
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from ding.envs import DingEnvWrapper, SubprocessEnvManagerV2 |
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from ding.data import DequeBuffer |
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from ding.config import compile_config |
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from ding.framework import task, ding_init |
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from ding.framework.context import OnlineRLContext |
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from ding.framework.middleware import OffPolicyLearner, StepCollector, interaction_evaluator, data_pusher, \ |
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eps_greedy_handler, CkptSaver, context_exchanger, model_exchanger, termination_checker, nstep_reward_enhancer, \ |
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online_logger |
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from ding.utils import set_pkg_seed |
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from dizoo.atari.envs.atari_env import AtariEnv |
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from dizoo.atari.config.serial.pong.pong_dqn_config import main_config, create_config |
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def main(): |
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logging.getLogger().setLevel(logging.INFO) |
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main_config.exp_name = 'pong_dqn_seed0_dist_rdma' |
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cfg = compile_config(main_config, create_cfg=create_config, auto=True) |
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ding_init(cfg) |
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with task.start(async_mode=False, ctx=OnlineRLContext()): |
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assert task.router.is_active, "Please execute this script with ditask! See note in the header." |
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set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) |
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model = DQN(**cfg.policy.model) |
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policy = DQNPolicy(cfg.policy, model=model) |
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if 'learner' in task.router.labels: |
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logging.info("Learner running on node {}".format(task.router.node_id)) |
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buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) |
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task.use( |
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context_exchanger( |
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send_keys=["train_iter"], |
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recv_keys=["trajectories", "episodes", "env_step", "env_episode"], |
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skip_n_iter=0 |
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) |
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) |
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task.use(model_exchanger(model, is_learner=True)) |
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task.use(nstep_reward_enhancer(cfg)) |
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task.use(data_pusher(cfg, buffer_)) |
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task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) |
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task.use(CkptSaver(policy, cfg.exp_name, train_freq=1000)) |
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elif 'collector' in task.router.labels: |
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logging.info("Collector running on node {}".format(task.router.node_id)) |
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collector_cfg = deepcopy(cfg.env) |
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collector_cfg.is_train = True |
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collector_env = SubprocessEnvManagerV2( |
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env_fn=[lambda: AtariEnv(collector_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager |
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) |
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task.use( |
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context_exchanger( |
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send_keys=["trajectories", "episodes", "env_step", "env_episode"], |
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recv_keys=["train_iter"], |
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skip_n_iter=1 |
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) |
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) |
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task.use(model_exchanger(model, is_learner=False)) |
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task.use(eps_greedy_handler(cfg)) |
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task.use(StepCollector(cfg, policy.collect_mode, collector_env)) |
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task.use(termination_checker(max_env_step=int(1e7))) |
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else: |
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raise KeyError("invalid router labels: {}".format(task.router.labels)) |
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task.run() |
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if __name__ == "__main__": |
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main() |
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