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: 128.98 +/- 76.62
+      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 0x7f799226a200>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f799226a290>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f799226a320>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f799226a3b0>", "_build": "<function ActorCriticPolicy._build at 0x7f799226a440>", "forward": "<function ActorCriticPolicy.forward at 0x7f799226a4d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f799226a560>", "_predict": "<function ActorCriticPolicy._predict at 0x7f799226a5f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f799226a680>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f799226a710>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f799226a7a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f79922367b0>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1666392051547273820, "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": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVgRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI3o0FhUGZ/7+UhpRSlIwBbJRNbAGMAXSUR0CsK6/HHWBjdX2UKGgGaAloD0MI9pmzPuXwTUCUhpRSlGgVTegDaBZHQKwtnnlGPPt1fZQoaAZoCWgPQwgWaeId4NBTQJSGlFKUaBVN6ANoFkdArC6wFaB7NXV9lChoBmgJaA9DCAQeGED4xVpAlIaUUpRoFU3oA2gWR0CsMMAhbGFSdX2UKGgGaAloD0MIurw5XKtRYkCUhpRSlGgVTegDaBZHQKwyLamoBJZ1fZQoaAZoCWgPQwjCbAIMy0FiQJSGlFKUaBVN6ANoFkdArDdtyvLX+XV9lChoBmgJaA9DCAZLdQEvyGBAlIaUUpRoFU3oA2gWR0CsOTD1GsmwdX2UKGgGaAloD0MIWwndJXF9XkCUhpRSlGgVTegDaBZHQKw5toouwot1fZQoaAZoCWgPQwheSfJcX2piQJSGlFKUaBVN6ANoFkdArDthO1v2oXV9lChoBmgJaA9DCGw9QzhmbTtAlIaUUpRoFU1KAWgWR0CsPb88kleGdX2UKGgGaAloD0MIPdNLjGVbW0CUhpRSlGgVTegDaBZHQKw+V4xDb8F1fZQoaAZoCWgPQwgjSnuDL1hdQJSGlFKUaBVN6ANoFkdArEnI+KTB7HV9lChoBmgJaA9DCFMFo5I6qF1AlIaUUpRoFU3oA2gWR0CsSmV58jRldX2UKGgGaAloD0MIglSKHY1/WUCUhpRSlGgVTegDaBZHQKxMFfUF0Pp1fZQoaAZoCWgPQwjw2xDjNZ1QQJSGlFKUaBVN6ANoFkdArE8vX7Lt/nV9lChoBmgJaA9DCPvnacAg7FdAlIaUUpRoFU3oA2gWR0CsVIoTGo73dX2UKGgGaAloD0MI4qsdxTnCXECUhpRSlGgVTegDaBZHQKxWnqVQhwF1fZQoaAZoCWgPQwh7avXVVSFaQJSGlFKUaBVN6ANoFkdArF2O4b0e2nV9lChoBmgJaA9DCOgTeZJ00F5AlIaUUpRoFU3oA2gWR0CsXx0VJtiydX2UKGgGaAloD0MI8bp+we6tYUCUhpRSlGgVTegDaBZHQKxgV1p0wJx1fZQoaAZoCWgPQwiH+l3YmjhZQJSGlFKUaBVN6ANoFkdArGR3L7oB73V9lChoBmgJaA9DCHb/WIgOSFxAlIaUUpRoFU3oA2gWR0CsaqBAOavzdX2UKGgGaAloD0MIiA0WTtL3XECUhpRSlGgVTegDaBZHQKxsqFotcwB1fZQoaAZoCWgPQwih9IWQ8+NXQJSGlFKUaBVN6ANoFkdArG0vCl7+k3V9lChoBmgJaA9DCJxPHauUUlpAlIaUUpRoFU3oA2gWR0Csbx/zz3AVdX2UKGgGaAloD0MI/RadLLXUX0CUhpRSlGgVTegDaBZHQKxxq5hBqsV1fZQoaAZoCWgPQwgTKji8IKFhQJSGlFKUaBVN6ANoFkdArHI4k7fYSXV9lChoBmgJaA9DCP7RN2kaJFdAlIaUUpRoFU3oA2gWR0CsdCLMLWqcdX2UKGgGaAloD0MIEOZ2L/ddTECUhpRSlGgVTegDaBZHQKx+SXoC+111fZQoaAZoCWgPQwgIdCZtqlRNQJSGlFKUaBVN6ANoFkdArIAYJokAxXV9lChoBmgJaA9DCKTFGcOchFlAlIaUUpRoFU3oA2gWR0CsgzsPatcOdX2UKGgGaAloD0MINV1PdF14Q8CUhpRSlGgVTV8BaBZHQKyDlAmAskJ1fZQoaAZoCWgPQwj2l92Th2hZQJSGlFKUaBVN6ANoFkdArIiHUvwmV3V9lChoBmgJaA9DCKN1VDVBtFZAlIaUUpRoFU3oA2gWR0CsipYtHxz8dX2UKGgGaAloD0MI5E7pYP0OW0CUhpRSlGgVTegDaBZHQKyRRZbILgJ1fZQoaAZoCWgPQwjaAGxAhGtgQJSGlFKUaBVN6ANoFkdArJLD5XU6P3V9lChoBmgJaA9DCC3SxDvAcWFAlIaUUpRoFU3oA2gWR0Csk/QF9roGdX2UKGgGaAloD0MIcjYdAdwBYkCUhpRSlGgVTegDaBZHQKyX4xKxs2x1fZQoaAZoCWgPQwhvS+SCM+ZdQJSGlFKUaBVN6ANoFkdArJ3R7Z39rHV9lChoBmgJaA9DCN3OvvIgdVhAlIaUUpRoFU3oA2gWR0CsoF4jSofkdX2UKGgGaAloD0MIpTFaR1VZWkCUhpRSlGgVTegDaBZHQKyiRtXPqs51fZQoaAZoCWgPQwjAzk2bca43QJSGlFKUaBVNcwFoFkdArKNg8U21lXV9lChoBmgJaA9DCJoklpS7/VxAlIaUUpRoFU3oA2gWR0CspN4NZvDQdX2UKGgGaAloD0MI17/rM2dyXkCUhpRSlGgVTegDaBZHQKyld9iMHbB1fZQoaAZoCWgPQwi9baZCPCVWQJSGlFKUaBVN6ANoFkdArKdKziS7oXV9lChoBmgJaA9DCAA7N23GbVlAlIaUUpRoFU3oA2gWR0Csp+nLq2SddX2UKGgGaAloD0MI5BWInpR3WkCUhpRSlGgVTegDaBZHQKyzbbHIZIh1fZQoaAZoCWgPQwh1BduIJ2NfQJSGlFKUaBVN6ANoFkdArLbXRoh6jXV9lChoBmgJaA9DCBVVv9L5Bl1AlIaUUpRoFU3oA2gWR0CstzyB9TgmdX2UKGgGaAloD0MI0Vs8vOcLY0CUhpRSlGgVTegDaBZHQKy8i1mapgl1fZQoaAZoCWgPQwgnh086kS9ZQJSGlFKUaBVN6ANoFkdArL69fVqesnV9lChoBmgJaA9DCA7ABkSIUUlAlIaUUpRoFU1pAWgWR0CswArzPKMedX2UKGgGaAloD0MInKc65Gb0XUCUhpRSlGgVTegDaBZHQKzFmcqe9SN1fZQoaAZoCWgPQwiH26FhMX9hQJSGlFKUaBVN6ANoFkdArMheMhouf3V9lChoBmgJaA9DCGPt72yPUFxAlIaUUpRoFU3oA2gWR0CszKIduHerdX2UKGgGaAloD0MI0ZDxKJWsU0CUhpRSlGgVTegDaBZHQKzS5iWmgrZ1fZQoaAZoCWgPQwjTo6mezIVaQJSGlFKUaBVN6ANoFkdArNWK2OQyRHV9lChoBmgJaA9DCGiVmdL6v2BAlIaUUpRoFU3oA2gWR0Cs16kuYhMbdX2UKGgGaAloD0MIaF4Ou++VXkCUhpRSlGgVTegDaBZHQKzY5RNRFZx1fZQoaAZoCWgPQwjJq3MMyLFaQJSGlFKUaBVN6ANoFkdArNp3VqesgnV9lChoBmgJaA9DCDZ4X5ULRF5AlIaUUpRoFU3oA2gWR0Cs2ydRJmNBdX2UKGgGaAloD0MICryTTw8yY0CUhpRSlGgVTegDaBZHQKzdGEOAiFF1fZQoaAZoCWgPQwimmllLAStYQJSGlFKUaBVN6ANoFkdArOkmZCv5g3V9lChoBmgJaA9DCNkkP+JXk1pAlIaUUpRoFU3oA2gWR0Cs7HzPa+N+dX2UKGgGaAloD0MI5DEDlfHPYECUhpRSlGgVTegDaBZHQKzs3k5IYm91fZQoaAZoCWgPQwiILqhvmYhbQJSGlFKUaBVN6ANoFkdArPHeQr+YMXV9lChoBmgJaA9DCF9/Ep87RltAlIaUUpRoFU3oA2gWR0Cs8+60IC2ddX2UKGgGaAloD0MI1/uNdtyFXkCUhpRSlGgVTegDaBZHQKz1HjuKGcp1fZQoaAZoCWgPQwiMEB5tnKFhQJSGlFKUaBVN6ANoFkdArPnCWkadc3V9lChoBmgJaA9DCC9SKAtfRzvAlIaUUpRoFU18AWgWR0Cs+3l0o0AMdX2UKGgGaAloD0MI3hyu1R5kYUCUhpRSlGgVTegDaBZHQKz8GZNO/L11fZQoaAZoCWgPQwi78lmeB6hYQJSGlFKUaBVN6ANoFkdArP+qttALRnV9lChoBmgJaA9DCEsd5PVgii7AlIaUUpRoFU06AWgWR0CtAH1EE1VHdX2UKGgGaAloD0MIelORCmP6WECUhpRSlGgVTegDaBZHQK0HGlyBCld1fZQoaAZoCWgPQwipiNNJto5RQJSGlFKUaBVN6ANoFkdArQp156dDpnV9lChoBmgJaA9DCLdif9k9qSNAlIaUUpRoFU03AWgWR0CtDIeJ53TvdX2UKGgGaAloD0MI9G4sKIw3YUCUhpRSlGgVTegDaBZHQK0M26iCaql1fZQoaAZoCWgPQwg25nXEIdhfQJSGlFKUaBVN6ANoFkdArQ3cl7dBSnV9lChoBmgJaA9DCCxEh8CRjVtAlIaUUpRoFU3oA2gWR0CtDyYd6sySdX2UKGgGaAloD0MIbr98smIHZUCUhpRSlGgVTegDaBZHQK0PqFKTSst1fZQoaAZoCWgPQwie6/twkFD2v5SGlFKUaBVNUQFoFkdArRFUUsWfsnV9lChoBmgJaA9DCATj4NIxLFpAlIaUUpRoFU3oA2gWR0CtEV5P/JeWdX2UKGgGaAloD0MI3WETmbn8WUCUhpRSlGgVTegDaBZHQK0ThXcxj8V1fZQoaAZoCWgPQwgFbAcjdsphQJSGlFKUaBVN6ANoFkdArSB8RzzVc3V9lChoBmgJaA9DCF6DvvT2al1AlIaUUpRoFU3oA2gWR0CtJW6kZaV2dX2UKGgGaAloD0MIQ8U4fxMYYUCUhpRSlGgVTegDaBZHQK0o2rSVnmJ1fZQoaAZoCWgPQwibOLnfoXgswJSGlFKUaBVNRAFoFkdArS4ZMxoIwHV9lChoBmgJaA9DCE2iXvBphWFAlIaUUpRoFU3oA2gWR0CtLkeqJdjYdX2UKGgGaAloD0MI+UhKehiGW0CUhpRSlGgVTegDaBZHQK0wLp/wy7B1fZQoaAZoCWgPQwjFceDVcp5SQJSGlFKUaBVN6ANoFkdArTStGI9C/3V9lChoBmgJaA9DCGjnNAu0xVpAlIaUUpRoFU3oA2gWR0CtOq3qZ+hHdX2UKGgGaAloD0MIhLweTIraUkCUhpRSlGgVTegDaBZHQK09PtMPBi11fZQoaAZoCWgPQwgCLPLrhx1YQJSGlFKUaBVN6ANoFkdArT7g1m8M/nV9lChoBmgJaA9DCBB39SoyYl9AlIaUUpRoFU3oA2gWR0CtPzd87ZFodX2UKGgGaAloD0MIFVW/0vldX0CUhpRSlGgVTegDaBZHQK1AQvHLidd1fZQoaAZoCWgPQwguHAjJAllYQJSGlFKUaBVN6ANoFkdArUGwH7gsLHV9lChoBmgJaA9DCIT0FDlEvltAlIaUUpRoFU3oA2gWR0CtQjUnPVurdX2UKGgGaAloD0MIWBtjJ7zULUCUhpRSlGgVTegDaBZHQK1D3loUSIx1fZQoaAZoCWgPQwhSD9HoDpRRQJSGlFKUaBVN6ANoFkdArUPoXEZR9HV9lChoBmgJaA9DCICdmzbjuV9AlIaUUpRoFU3oA2gWR0CtRgdVFQVLdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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:a2a279c49a655950ea04f809880197555e7c0a264b3c4db6fdbbbdfcfc84c441
+size 147154

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 0x7f799226a200>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f799226a290>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f799226a320>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f799226a3b0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f799226a440>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f799226a4d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f799226a560>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f799226a5f0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f799226a680>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f799226a710>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f799226a7a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f79922367b0>"
+    },
+    "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": 507904,
+    "_total_timesteps": 500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1666392051547273820,
+    "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": -0.015808000000000044,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVgRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI3o0FhUGZ/7+UhpRSlIwBbJRNbAGMAXSUR0CsK6/HHWBjdX2UKGgGaAloD0MI9pmzPuXwTUCUhpRSlGgVTegDaBZHQKwtnnlGPPt1fZQoaAZoCWgPQwgWaeId4NBTQJSGlFKUaBVN6ANoFkdArC6wFaB7NXV9lChoBmgJaA9DCAQeGED4xVpAlIaUUpRoFU3oA2gWR0CsMMAhbGFSdX2UKGgGaAloD0MIurw5XKtRYkCUhpRSlGgVTegDaBZHQKwyLamoBJZ1fZQoaAZoCWgPQwjCbAIMy0FiQJSGlFKUaBVN6ANoFkdArDdtyvLX+XV9lChoBmgJaA9DCAZLdQEvyGBAlIaUUpRoFU3oA2gWR0CsOTD1GsmwdX2UKGgGaAloD0MIWwndJXF9XkCUhpRSlGgVTegDaBZHQKw5toouwot1fZQoaAZoCWgPQwheSfJcX2piQJSGlFKUaBVN6ANoFkdArDthO1v2oXV9lChoBmgJaA9DCGw9QzhmbTtAlIaUUpRoFU1KAWgWR0CsPb88kleGdX2UKGgGaAloD0MIPdNLjGVbW0CUhpRSlGgVTegDaBZHQKw+V4xDb8F1fZQoaAZoCWgPQwgjSnuDL1hdQJSGlFKUaBVN6ANoFkdArEnI+KTB7HV9lChoBmgJaA9DCFMFo5I6qF1AlIaUUpRoFU3oA2gWR0CsSmV58jRldX2UKGgGaAloD0MIglSKHY1/WUCUhpRSlGgVTegDaBZHQKxMFfUF0Pp1fZQoaAZoCWgPQwjw2xDjNZ1QQJSGlFKUaBVN6ANoFkdArE8vX7Lt/nV9lChoBmgJaA9DCPvnacAg7FdAlIaUUpRoFU3oA2gWR0CsVIoTGo73dX2UKGgGaAloD0MI4qsdxTnCXECUhpRSlGgVTegDaBZHQKxWnqVQhwF1fZQoaAZoCWgPQwh7avXVVSFaQJSGlFKUaBVN6ANoFkdArF2O4b0e2nV9lChoBmgJaA9DCOgTeZJ00F5AlIaUUpRoFU3oA2gWR0CsXx0VJtiydX2UKGgGaAloD0MI8bp+we6tYUCUhpRSlGgVTegDaBZHQKxgV1p0wJx1fZQoaAZoCWgPQwiH+l3YmjhZQJSGlFKUaBVN6ANoFkdArGR3L7oB73V9lChoBmgJaA9DCHb/WIgOSFxAlIaUUpRoFU3oA2gWR0CsaqBAOavzdX2UKGgGaAloD0MIiA0WTtL3XECUhpRSlGgVTegDaBZHQKxsqFotcwB1fZQoaAZoCWgPQwih9IWQ8+NXQJSGlFKUaBVN6ANoFkdArG0vCl7+k3V9lChoBmgJaA9DCJxPHauUUlpAlIaUUpRoFU3oA2gWR0Csbx/zz3AVdX2UKGgGaAloD0MI/RadLLXUX0CUhpRSlGgVTegDaBZHQKxxq5hBqsV1fZQoaAZoCWgPQwgTKji8IKFhQJSGlFKUaBVN6ANoFkdArHI4k7fYSXV9lChoBmgJaA9DCP7RN2kaJFdAlIaUUpRoFU3oA2gWR0CsdCLMLWqcdX2UKGgGaAloD0MIEOZ2L/ddTECUhpRSlGgVTegDaBZHQKx+SXoC+111fZQoaAZoCWgPQwgIdCZtqlRNQJSGlFKUaBVN6ANoFkdArIAYJokAxXV9lChoBmgJaA9DCKTFGcOchFlAlIaUUpRoFU3oA2gWR0CsgzsPatcOdX2UKGgGaAloD0MINV1PdF14Q8CUhpRSlGgVTV8BaBZHQKyDlAmAskJ1fZQoaAZoCWgPQwj2l92Th2hZQJSGlFKUaBVN6ANoFkdArIiHUvwmV3V9lChoBmgJaA9DCKN1VDVBtFZAlIaUUpRoFU3oA2gWR0CsipYtHxz8dX2UKGgGaAloD0MI5E7pYP0OW0CUhpRSlGgVTegDaBZHQKyRRZbILgJ1fZQoaAZoCWgPQwjaAGxAhGtgQJSGlFKUaBVN6ANoFkdArJLD5XU6P3V9lChoBmgJaA9DCC3SxDvAcWFAlIaUUpRoFU3oA2gWR0Csk/QF9roGdX2UKGgGaAloD0MIcjYdAdwBYkCUhpRSlGgVTegDaBZHQKyX4xKxs2x1fZQoaAZoCWgPQwhvS+SCM+ZdQJSGlFKUaBVN6ANoFkdArJ3R7Z39rHV9lChoBmgJaA9DCN3OvvIgdVhAlIaUUpRoFU3oA2gWR0CsoF4jSofkdX2UKGgGaAloD0MIpTFaR1VZWkCUhpRSlGgVTegDaBZHQKyiRtXPqs51fZQoaAZoCWgPQwjAzk2bca43QJSGlFKUaBVNcwFoFkdArKNg8U21lXV9lChoBmgJaA9DCJoklpS7/VxAlIaUUpRoFU3oA2gWR0CspN4NZvDQdX2UKGgGaAloD0MI17/rM2dyXkCUhpRSlGgVTegDaBZHQKyld9iMHbB1fZQoaAZoCWgPQwi9baZCPCVWQJSGlFKUaBVN6ANoFkdArKdKziS7oXV9lChoBmgJaA9DCAA7N23GbVlAlIaUUpRoFU3oA2gWR0Csp+nLq2SddX2UKGgGaAloD0MI5BWInpR3WkCUhpRSlGgVTegDaBZHQKyzbbHIZIh1fZQoaAZoCWgPQwh1BduIJ2NfQJSGlFKUaBVN6ANoFkdArLbXRoh6jXV9lChoBmgJaA9DCBVVv9L5Bl1AlIaUUpRoFU3oA2gWR0CstzyB9TgmdX2UKGgGaAloD0MI0Vs8vOcLY0CUhpRSlGgVTegDaBZHQKy8i1mapgl1fZQoaAZoCWgPQwgnh086kS9ZQJSGlFKUaBVN6ANoFkdArL69fVqesnV9lChoBmgJaA9DCA7ABkSIUUlAlIaUUpRoFU1pAWgWR0CswArzPKMedX2UKGgGaAloD0MInKc65Gb0XUCUhpRSlGgVTegDaBZHQKzFmcqe9SN1fZQoaAZoCWgPQwiH26FhMX9hQJSGlFKUaBVN6ANoFkdArMheMhouf3V9lChoBmgJaA9DCGPt72yPUFxAlIaUUpRoFU3oA2gWR0CszKIduHerdX2UKGgGaAloD0MI0ZDxKJWsU0CUhpRSlGgVTegDaBZHQKzS5iWmgrZ1fZQoaAZoCWgPQwjTo6mezIVaQJSGlFKUaBVN6ANoFkdArNWK2OQyRHV9lChoBmgJaA9DCGiVmdL6v2BAlIaUUpRoFU3oA2gWR0Cs16kuYhMbdX2UKGgGaAloD0MIaF4Ou++VXkCUhpRSlGgVTegDaBZHQKzY5RNRFZx1fZQoaAZoCWgPQwjJq3MMyLFaQJSGlFKUaBVN6ANoFkdArNp3VqesgnV9lChoBmgJaA9DCDZ4X5ULRF5AlIaUUpRoFU3oA2gWR0Cs2ydRJmNBdX2UKGgGaAloD0MICryTTw8yY0CUhpRSlGgVTegDaBZHQKzdGEOAiFF1fZQoaAZoCWgPQwimmllLAStYQJSGlFKUaBVN6ANoFkdArOkmZCv5g3V9lChoBmgJaA9DCNkkP+JXk1pAlIaUUpRoFU3oA2gWR0Cs7HzPa+N+dX2UKGgGaAloD0MI5DEDlfHPYECUhpRSlGgVTegDaBZHQKzs3k5IYm91fZQoaAZoCWgPQwiILqhvmYhbQJSGlFKUaBVN6ANoFkdArPHeQr+YMXV9lChoBmgJaA9DCF9/Ep87RltAlIaUUpRoFU3oA2gWR0Cs8+60IC2ddX2UKGgGaAloD0MI1/uNdtyFXkCUhpRSlGgVTegDaBZHQKz1HjuKGcp1fZQoaAZoCWgPQwiMEB5tnKFhQJSGlFKUaBVN6ANoFkdArPnCWkadc3V9lChoBmgJaA9DCC9SKAtfRzvAlIaUUpRoFU18AWgWR0Cs+3l0o0AMdX2UKGgGaAloD0MI3hyu1R5kYUCUhpRSlGgVTegDaBZHQKz8GZNO/L11fZQoaAZoCWgPQwi78lmeB6hYQJSGlFKUaBVN6ANoFkdArP+qttALRnV9lChoBmgJaA9DCEsd5PVgii7AlIaUUpRoFU06AWgWR0CtAH1EE1VHdX2UKGgGaAloD0MIelORCmP6WECUhpRSlGgVTegDaBZHQK0HGlyBCld1fZQoaAZoCWgPQwipiNNJto5RQJSGlFKUaBVN6ANoFkdArQp156dDpnV9lChoBmgJaA9DCLdif9k9qSNAlIaUUpRoFU03AWgWR0CtDIeJ53TvdX2UKGgGaAloD0MI9G4sKIw3YUCUhpRSlGgVTegDaBZHQK0M26iCaql1fZQoaAZoCWgPQwg25nXEIdhfQJSGlFKUaBVN6ANoFkdArQ3cl7dBSnV9lChoBmgJaA9DCCxEh8CRjVtAlIaUUpRoFU3oA2gWR0CtDyYd6sySdX2UKGgGaAloD0MIbr98smIHZUCUhpRSlGgVTegDaBZHQK0PqFKTSst1fZQoaAZoCWgPQwie6/twkFD2v5SGlFKUaBVNUQFoFkdArRFUUsWfsnV9lChoBmgJaA9DCATj4NIxLFpAlIaUUpRoFU3oA2gWR0CtEV5P/JeWdX2UKGgGaAloD0MI3WETmbn8WUCUhpRSlGgVTegDaBZHQK0ThXcxj8V1fZQoaAZoCWgPQwgFbAcjdsphQJSGlFKUaBVN6ANoFkdArSB8RzzVc3V9lChoBmgJaA9DCF6DvvT2al1AlIaUUpRoFU3oA2gWR0CtJW6kZaV2dX2UKGgGaAloD0MIQ8U4fxMYYUCUhpRSlGgVTegDaBZHQK0o2rSVnmJ1fZQoaAZoCWgPQwibOLnfoXgswJSGlFKUaBVNRAFoFkdArS4ZMxoIwHV9lChoBmgJaA9DCE2iXvBphWFAlIaUUpRoFU3oA2gWR0CtLkeqJdjYdX2UKGgGaAloD0MI+UhKehiGW0CUhpRSlGgVTegDaBZHQK0wLp/wy7B1fZQoaAZoCWgPQwjFceDVcp5SQJSGlFKUaBVN6ANoFkdArTStGI9C/3V9lChoBmgJaA9DCGjnNAu0xVpAlIaUUpRoFU3oA2gWR0CtOq3qZ+hHdX2UKGgGaAloD0MIhLweTIraUkCUhpRSlGgVTegDaBZHQK09PtMPBi11fZQoaAZoCWgPQwgCLPLrhx1YQJSGlFKUaBVN6ANoFkdArT7g1m8M/nV9lChoBmgJaA9DCBB39SoyYl9AlIaUUpRoFU3oA2gWR0CtPzd87ZFodX2UKGgGaAloD0MIFVW/0vldX0CUhpRSlGgVTegDaBZHQK1AQvHLidd1fZQoaAZoCWgPQwguHAjJAllYQJSGlFKUaBVN6ANoFkdArUGwH7gsLHV9lChoBmgJaA9DCIT0FDlEvltAlIaUUpRoFU3oA2gWR0CtQjUnPVurdX2UKGgGaAloD0MIWBtjJ7zULUCUhpRSlGgVTegDaBZHQK1D3loUSIx1fZQoaAZoCWgPQwhSD9HoDpRRQJSGlFKUaBVN6ANoFkdArUPoXEZR9HV9lChoBmgJaA9DCICdmzbjuV9AlIaUUpRoFU3oA2gWR0CtRgdVFQVLdWUu"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 124,
+    "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
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:70bf061ccde89ae4b65c31758b9ef6fcc31e6fed770d2cc01e9eec7815f6194a
+size 87865

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2adbc93ffd8172bca08305ce09991c3b46b500621f48f7df99cc9a883baccbed
+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": 128.9817455245529, "std_reward": 76.61958898590055, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-21T22:56:15.850594"}