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feature(nyz): add new pipeline impala demo
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import gym | ||
from ditk import logging | ||
from ding.model import VAC | ||
from ding.policy import IMPALAPolicy | ||
from ding.envs import DingEnvWrapper, BaseEnvManagerV2 | ||
from ding.data import DequeBuffer | ||
from ding.config import compile_config | ||
from ding.framework import task | ||
from ding.framework.context import OnlineRLContext | ||
from ding.framework.middleware import OffPolicyLearner, StepCollector, interaction_evaluator, data_pusher, \ | ||
CkptSaver | ||
from ding.utils import set_pkg_seed | ||
from dizoo.classic_control.cartpole.config.cartpole_impala_config import main_config, create_config | ||
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def main(): | ||
logging.getLogger().setLevel(logging.INFO) | ||
cfg = compile_config(main_config, create_cfg=create_config, auto=True) | ||
with task.start(async_mode=False, ctx=OnlineRLContext()): | ||
collector_env = BaseEnvManagerV2( | ||
env_fn=[lambda: DingEnvWrapper(gym.make("CartPole-v0")) for _ in range(cfg.env.collector_env_num)], | ||
cfg=cfg.env.manager | ||
) | ||
evaluator_env = BaseEnvManagerV2( | ||
env_fn=[lambda: DingEnvWrapper(gym.make("CartPole-v0")) for _ in range(cfg.env.evaluator_env_num)], | ||
cfg=cfg.env.manager | ||
) | ||
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set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) | ||
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model = VAC(**cfg.policy.model) | ||
buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) | ||
policy = IMPALAPolicy(cfg.policy, model=model) | ||
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task.use(interaction_evaluator(cfg, policy.eval_mode, evaluator_env)) | ||
task.use(StepCollector(cfg, policy.collect_mode, collector_env)) | ||
task.use(data_pusher(cfg, buffer_, group_by_env=True)) | ||
task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) | ||
task.use(CkptSaver(policy, cfg.exp_name, train_freq=100)) | ||
task.run() | ||
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if __name__ == "__main__": | ||
main() |
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