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https://github.com/vale981/ray
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28 lines
739 B
YAML
28 lines
739 B
YAML
# On a single GPU, this achieves maximum reward in ~15-20 minutes.
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#
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# $ python train.py -f tuned_configs/pong-ppo.yaml
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#
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pong-ppo:
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env: PongNoFrameskip-v4
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run: PPO
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config:
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# Works for both torch and tf.
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framework: tf
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lambda: 0.95
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kl_coeff: 0.5
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clip_rewards: True
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clip_param: 0.1
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vf_clip_param: 10.0
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entropy_coeff: 0.01
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train_batch_size: 5000
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rollout_fragment_length: 20
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sgd_minibatch_size: 500
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num_sgd_iter: 10
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num_workers: 32
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num_envs_per_worker: 5
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batch_mode: truncate_episodes
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observation_filter: NoFilter
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num_gpus: 1
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model:
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dim: 42
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vf_share_layers: true
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