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Browse files- .gitattributes +1 -0
- config.json +1 -0
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +94 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/system_info.txt +7 -0
- results.json +1 -0
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If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7fb4b5283710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb4b52837a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb4b5283830>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb4b52838c0>", "_build": "<function ActorCriticPolicy._build at 0x7fb4b5283950>", "forward": "<function ActorCriticPolicy.forward at 0x7fb4b52839e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb4b5283a70>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb4b5283b00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb4b5283b90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb4b5283c20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb4b5283cb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fb4b52a8180>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": 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"target_kl": null
|
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ppo-LunarLander-v2/policy.optimizer.pth
ADDED
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|
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version https://git-lfs.github.com/spec/v1
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oid sha256:3c8c173b2e034cba75cc96762cbbfd3eec89b95732c1ef6a5e0c43d200d223b9
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ppo-LunarLander-v2/policy.pth
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:cb44b7e8c30deb683aeb87a2c1d8672bc847e7e61cf35674e2e91e1d42709082
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size 43201
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ppo-LunarLander-v2/pytorch_variables.pth
ADDED
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ppo-LunarLander-v2/system_info.txt
ADDED
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OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
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Python: 3.7.13
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Stable-Baselines3: 1.5.0
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PyTorch: 1.11.0+cu113
|
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GPU Enabled: True
|
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Numpy: 1.21.6
|
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Gym: 0.21.0
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results.json
ADDED
@@ -0,0 +1 @@
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|
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{"mean_reward": 121.5986761643288, "std_reward": 59.316103219650024, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-19T15:00:12.073625"}
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