wehub-resource-sync
32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
# The currently Ray RLlib-accepted PPO config to be used when restoring from an
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# older checkpoint (possibly from an older python version) and having to bring the
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# algo config along.
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# Change this file, whenever there are changes in the config API, such as naming
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# changes, etc.. RLlib's `Checkpointable` class should be resilient against such
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# changes.
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from ray.rllib.algorithms.ppo import PPOConfig
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from ray.rllib.core.rl_module.default_model_config import DefaultModelConfig
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from ray.rllib.examples.envs.classes.multi_agent import MultiAgentCartPole
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from ray.tune import register_env
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register_env("multi_agent_cartpole", lambda cfg: MultiAgentCartPole(config=cfg))
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config = (
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PPOConfig()
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.environment("multi_agent_cartpole", env_config={"num_agents": 2})
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# Keep things very small.
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.rl_module(
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model_config=DefaultModelConfig(fcnet_hiddens=[16]),
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algorithm_config_overrides_per_module={
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"p0": PPOConfig.overrides(lr=0.00005),
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"p1": PPOConfig.overrides(lr=0.0001),
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},
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)
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.multi_agent(
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policy_mapping_fn=lambda aid, *arg, **kw: f"p{aid}",
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policies={"p0", "p1"},
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)
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)
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