wehub-resource-sync
48 lines
1.3 KiB
Python
48 lines
1.3 KiB
Python
from ray.rllib.algorithms.appo import APPOConfig
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from ray.rllib.connectors.env_to_module.mean_std_filter import MeanStdFilter
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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.stateless_cartpole import StatelessCartPole
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from ray.rllib.examples.utils import (
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add_rllib_example_script_args,
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run_rllib_example_script_experiment,
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)
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parser = add_rllib_example_script_args(
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default_timesteps=2000000,
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default_reward=300.0,
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)
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parser.set_defaults(
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num_env_runners=3,
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)
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# Use `parser` to add your own custom command line options to this script
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# and (if needed) use their values to set up `config` below.
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args = parser.parse_args()
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config = (
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APPOConfig()
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.environment(StatelessCartPole)
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.env_runners(
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env_to_module_connector=lambda env, spaces, device: MeanStdFilter(),
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)
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.training(
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lr=0.0005 * ((args.num_learners or 1) ** 0.5),
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num_epochs=1,
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vf_loss_coeff=0.05,
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entropy_coeff=0.005,
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use_circular_buffer=False,
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broadcast_interval=10,
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)
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.rl_module(
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model_config=DefaultModelConfig(
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vf_share_layers=True,
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use_lstm=True,
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max_seq_len=20,
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),
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)
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)
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if __name__ == "__main__":
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run_rllib_example_script_experiment(config, args)
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