Upload PPO LunarLander-v2 trained agent

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: -143.84 +/- 61.38
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **LunarLander-v2**
+This is a trained model of a **PPO** agent playing **LunarLander-v2**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

@@ -0,0 +1 @@
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. 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 0x7fabe9010f80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fabe9013050>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fabe90130e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fabe9013170>", "_build": "<function ActorCriticPolicy._build at 0x7fabe9013200>", "forward": "<function ActorCriticPolicy.forward at 0x7fabe9013290>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fabe9013320>", "_predict": "<function ActorCriticPolicy._predict at 0x7fabe90133b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fabe9013440>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fabe90134d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fabe9013560>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fabe8fd6e40>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 114688, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1668496682293300524, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.1468799999999999, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIoDL+fcYBUMCUhpRSlIwBbJRLSowBdJRHQHUNTxPO6d11fZQoaAZoCWgPQwgmN4qsNbhMwJSGlFKUaBVLbGgWR0B1DafGuLaVdX2UKGgGaAloD0MId700RYADT8CUhpRSlGgVS2NoFkdAdQ5NmDlHSXV9lChoBmgJaA9DCOI8nMB0GE/AlIaUUpRoFUt1aBZHQHUOxew9q1x1fZQoaAZoCWgPQwiitDf4wrpHwJSGlFKUaBVLe2gWR0B1DwGu9vjwdX2UKGgGaAloD0MIp3hcVIuUTMCUhpRSlGgVS0loFkdAdQ8TUiILxHV9lChoBmgJaA9DCAw6IXTQFFDAlIaUUpRoFUtjaBZHQHUPDTz/ZNB1fZQoaAZoCWgPQwhpHsAivzZUwJSGlFKUaBVLZ2gWR0B1D02itaIOdX2UKGgGaAloD0MIfc7drpfeSMCUhpRSlGgVS2JoFkdAdQ+DtgKF7HV9lChoBmgJaA9DCDQUd7zJIFXAlIaUUpRoFUtxaBZHQHUP1tj0+Tx1fZQoaAZoCWgPQwjPEmQEVFNRwJSGlFKUaBVLT2gWR0B1ED5VOsT4dX2UKGgGaAloD0MIZJY9CWzqPcCUhpRSlGgVS29oFkdAdRCOBUaQ3nV9lChoBmgJaA9DCJ1Hxf8d4U7AlIaUUpRoFUtPaBZHQHURQkX1rZd1fZQoaAZoCWgPQwjwTj49tg5TwJSGlFKUaBVLc2gWR0B1EkH2RJVbdX2UKGgGaAloD0MIl4+kpIeFQsCUhpRSlGgVS15oFkdAdRKm7aqS5nV9lChoBmgJaA9DCDrq6LgaklLAlIaUUpRoFUtdaBZHQHUTdl2/zrh1fZQoaAZoCWgPQwh9emzLgKNPwJSGlFKUaBVLZGgWR0B1E5byH2ytdX2UKGgGaAloD0MId01IawwyT8CUhpRSlGgVS0ZoFkdAdRQwPiDM/3V9lChoBmgJaA9DCAMF3smnWVbAlIaUUpRoFUtTaBZHQHUUc6NlyzZ1fZQoaAZoCWgPQwiloUYhyfZdwJSGlFKUaBVLZWgWR0B1FStknTiLdX2UKGgGaAloD0MITODW3TxLWMCUhpRSlGgVS1VoFkdAdRWizcAR03V9lChoBmgJaA9DCA8r3PKRLDHAlIaUUpRoFUtgaBZHQHUVmZVn27F1fZQoaAZoCWgPQwiMEB5tHMtcwJSGlFKUaBVLl2gWR0B1FdI8QqZudX2UKGgGaAloD0MIOWQD6WJJXcCUhpRSlGgVS2xoFkdAdRX3IuGsWHV9lChoBmgJaA9DCBrfF5eqqljAlIaUUpRoFUtuaBZHQHUWDho/Rmd1fZQoaAZoCWgPQwjWV1cFartWwJSGlFKUaBVLfWgWR0B1FlOVPepGdX2UKGgGaAloD0MIb/JbdLKuS8CUhpRSlGgVS3VoFkdAdRZ+B6KLsXV9lChoBmgJaA9DCMKKU62FuUHAlIaUUpRoFUt5aBZHQHUYYKhL5AR1fZQoaAZoCWgPQwhvSnmthFhOwJSGlFKUaBVLaGgWR0B1GRUVBUrDdX2UKGgGaAloD0MIH6FmSBXiUsCUhpRSlGgVS1JoFkdAdRkOJcgQpXV9lChoBmgJaA9DCH3NctnojVbAlIaUUpRoFUtWaBZHQHUZNBF/hEV1fZQoaAZoCWgPQwgNF7mnK55jwJSGlFKUaBVLf2gWR0B1GYX+ERJ3dX2UKGgGaAloD0MIXp7OFaUAVcCUhpRSlGgVS1FoFkdAdRnWM0gr6XV9lChoBmgJaA9DCCZTBaOSqVXAlIaUUpRoFUtyaBZHQHUaKuB+Wnl1fZQoaAZoCWgPQwiOc5twrxA+wJSGlFKUaBVLSmgWR0B1GhPqLS/kdX2UKGgGaAloD0MIJt9sc2PAS8CUhpRSlGgVS0xoFkdAdRqh1klNUXV9lChoBmgJaA9DCMe8jjhkll7AlIaUUpRoFUtlaBZHQHUa29L6DXh1fZQoaAZoCWgPQwhEigESTbZWwJSGlFKUaBVLY2gWR0B1HFZwGW2PdX2UKGgGaAloD0MIam0a22vROECUhpRSlGgVS2BoFkdAdRy1MM7U5XV9lChoBmgJaA9DCLHh6ZWyqVLAlIaUUpRoFUt2aBZHQHUdSlnAZbZ1fZQoaAZoCWgPQwhaZ3xfXFRNwJSGlFKUaBVLdWgWR0B1HXJNj9XLdX2UKGgGaAloD0MIjqz8MhhdRMCUhpRSlGgVS0poFkdAdR3Z62OQyXV9lChoBmgJaA9DCC3MQjunr03AlIaUUpRoFUt0aBZHQHUd4Z2pyZN1fZQoaAZoCWgPQwiiDcAGRNgWQJSGlFKUaBVLhGgWR0B1HpaPjn3ddX2UKGgGaAloD0MIQ6z+CMNWV8CUhpRSlGgVS1BoFkdAdR6s+FDfFnV9lChoBmgJaA9DCDL/6Js0lVPAlIaUUpRoFUtKaBZHQHUe0NnXd0t1fZQoaAZoCWgPQwh3hNOCF0xcwJSGlFKUaBVLVWgWR0B1H5/ViF0xdX2UKGgGaAloD0MIfZOmQdEPUcCUhpRSlGgVS3BoFkdAdSBRbbDdg3V9lChoBmgJaA9DCPwdigL9+mXAlIaUUpRoFUt9aBZHQHUggWBSUC91fZQoaAZoCWgPQwjo9/2bl5NjwJSGlFKUaBVLYGgWR0B1INYoy9EkdX2UKGgGaAloD0MIyD8ziA/oWsCUhpRSlGgVS0doFkdAdSD8zyjHn3V9lChoBmgJaA9DCL9hokEKiErAlIaUUpRoFUt1aBZHQHUhZCWu5jJ1fZQoaAZoCWgPQwjovwevXeZUwJSGlFKUaBVLY2gWR0B1IUcp9ZzQdX2UKGgGaAloD0MItvY+VYWWM8CUhpRSlGgVS4VoFkdAdSHHM2WIGnV9lChoBmgJaA9DCMjT8gNXNlfAlIaUUpRoFUtVaBZHQHUiNjslb/x1fZQoaAZoCWgPQwiHo6t0d6VSwJSGlFKUaBVLVGgWR0B1Iq3b212JdX2UKGgGaAloD0MI3o0FhUHbXMCUhpRSlGgVS09oFkdAdSLq9XcQAnV9lChoBmgJaA9DCAaf5uRFbVbAlIaUUpRoFUtHaBZHQHUjJCKJl8R1fZQoaAZoCWgPQwg6BI4EGjhGwJSGlFKUaBVLYmgWR0B1JA+Y+jdpdX2UKGgGaAloD0MIB5s6j4o2V8CUhpRSlGgVS1NoFkdAdSQZjhDPW3V9lChoBmgJaA9DCONuEK0VG1LAlIaUUpRoFUtYaBZHQHUlRxT850d1fZQoaAZoCWgPQwjHuU24V/ZfwJSGlFKUaBVLSWgWR0B1Jaro4dZJdX2UKGgGaAloD0MIJNHLKJZZWcCUhpRSlGgVS1RoFkdAdSZBSDRMOHV9lChoBmgJaA9DCM791eO+DTHAlIaUUpRoFUt1aBZHQHUmQEt/WlN1fZQoaAZoCWgPQwjFWRE10QZcwJSGlFKUaBVLU2gWR0B1JqFAVwgldX2UKGgGaAloD0MIXmdD/pnmV8CUhpRSlGgVS5BoFkdAdSa7vG6wuHV9lChoBmgJaA9DCNHN/kC5G0DAlIaUUpRoFUtbaBZHQHUnQiml67d1fZQoaAZoCWgPQwhNTu0M0zFgwJSGlFKUaBVLbmgWR0B1J5MzuWrwdX2UKGgGaAloD0MIgzKNJhfrTsCUhpRSlGgVS1RoFkdAdSejdpItlXV9lChoBmgJaA9DCMprJXSXOE/AlIaUUpRoFUuMaBZHQHUphArxy4p1fZQoaAZoCWgPQwizI9V3fhxYwJSGlFKUaBVLZGgWR0B1KdW6shgWdX2UKGgGaAloD0MIlDE+zF5bUcCUhpRSlGgVS3BoFkdAdSoo9LYf4nV9lChoBmgJaA9DCEG8rl+wUFjAlIaUUpRoFUuCaBZHQHUqagh8pkR1fZQoaAZoCWgPQwjqJFtdTjdRwJSGlFKUaBVLQGgWR0B1KqQo1DSgdX2UKGgGaAloD0MI4E237BBZTcCUhpRSlGgVS3VoFkdAdSrErGza9XV9lChoBmgJaA9DCANDVrd6AVHAlIaUUpRoFUtnaBZHQHUrDiwSrYJ1fZQoaAZoCWgPQwgEqn8QyQlYwJSGlFKUaBVLSWgWR0B1KzNOdoWYdX2UKGgGaAloD0MIGZC93v3RTsCUhpRSlGgVS3JoFkdAdSvDP4VRDXV9lChoBmgJaA9DCJp4B3jSh1fAlIaUUpRoFUtoaBZHQHUsQ2uPmxN1fZQoaAZoCWgPQwhat0Htt9xPwJSGlFKUaBVLU2gWR0B1LDSy+pOvdX2UKGgGaAloD0MIo3iVtU20VsCUhpRSlGgVS3hoFkdAdS2YTj/+9HV9lChoBmgJaA9DCHFWRE30ES7AlIaUUpRoFUtEaBZHQHUt6c7Qswt1fZQoaAZoCWgPQwhrgqj7AFdbwJSGlFKUaBVLamgWR0B1LrFWGRFJdX2UKGgGaAloD0MIdxVSflIzQcCUhpRSlGgVS4RoFkdAdS9+8oQWe3V9lChoBmgJaA9DCI4hADj2sEDAlIaUUpRoFUuDaBZHQHUwCWE9Mbp1fZQoaAZoCWgPQwixw5j098dVwJSGlFKUaBVLTmgWR0B1MDLKV6eHdX2UKGgGaAloD0MI1ub/VUcdZMCUhpRSlGgVS35oFkdAdTAeiSJTEXV9lChoBmgJaA9DCM1Xycfu0VHAlIaUUpRoFUtWaBZHQHUweCkGiYd1fZQoaAZoCWgPQwg8Mlab/71PwJSGlFKUaBVLWmgWR0B1MKAe7tiQdX2UKGgGaAloD0MIwR9+/nvMP8CUhpRSlGgVS2NoFkdAdTDH6uW8iHV9lChoBmgJaA9DCJsg6j4AolbAlIaUUpRoFUtiaBZHQHUw88DB/I91fZQoaAZoCWgPQwjScTWyK1JQwJSGlFKUaBVLUWgWR0B1MTlvIfbLdX2UKGgGaAloD0MIM6g2OBF7UcCUhpRSlGgVSz5oFkdAdTIih37k4nV9lChoBmgJaA9DCDc5fNKJQ1fAlIaUUpRoFUtnaBZHQHUzDGgi/wl1fZQoaAZoCWgPQwglsg+yLOhTwJSGlFKUaBVLbGgWR0B1M20a6z3RdX2UKGgGaAloD0MIpz/7kSKyB0CUhpRSlGgVS31oFkdAdTNxnnMdLnV9lChoBmgJaA9DCNoAbECEIkvAlIaUUpRoFUuaaBZHQHUz9ic5Ke11fZQoaAZoCWgPQwjd6c4Tz9NQwJSGlFKUaBVLS2gWR0B1NOAvtdAxdX2UKGgGaAloD0MIkIKnkCvFRsCUhpRSlGgVS2BoFkdAdTUATZg5R3V9lChoBmgJaA9DCPLNNjemAzXAlIaUUpRoFUtEaBZHQHU1dFWn0kJ1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 28, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ad734165591d0703d6fd0b9f28ac45f83d1f52a921d72d1ebdc9c103b43f8249
+size 147019

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

ppo-LunarLander-v2/data

@@ -0,0 +1,94 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
+        "__module__": "stable_baselines3.common.policies",
+        "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. 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 0x7fabe9010f80>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fabe9013050>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fabe90130e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fabe9013170>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fabe9013200>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fabe9013290>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fabe9013320>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fabe90133b0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fabe9013440>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fabe90134d0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fabe9013560>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fabe8fd6e40>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False]",
+        "bounded_above": "[False False False False False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        "n": 4,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 114688,
+    "_total_timesteps": 100000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1668496682293300524,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.1468799999999999,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 28,
+    "n_steps": 1024,
+    "gamma": 0.999,
+    "gae_lambda": 0.98,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 4,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0d38b4c48dd1b766eb1fbc11066ad7e74e78bb8e7d4c8cdf3aa7752b1ecf0edd
+size 87865

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e2b75f7a9b582268bf26255a5dc7b7db970479b1f6a9dcc2c1fe0e9ab4bed54b
+size 43201

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.7.15
+Stable-Baselines3: 1.6.2
+PyTorch: 1.12.1+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": -143.84413400135236, "std_reward": 61.3771401487424, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-11-15T07:40:52.891582"}