ivi137 commited on
Commit
988d112
·
1 Parent(s): 4265dbc

Upload PPO LunarLander-v2

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 268.90 +/- 12.66
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
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 0x7fd17d894ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd17d894d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd17d894dc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd17d894e50>", "_build": "<function ActorCriticPolicy._build at 0x7fd17d894ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7fd17d894f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd17d818040>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd17d8180d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd17d818160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd17d8181f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd17d818280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fd17d8915d0>"}, "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": 1376256, "_total_timesteps": 1370000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1672428097806757523, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJP2dL6bOMg+n5eOPsX51b5wa7I6bpTIPQAAAAAAAAAAzfQMOzEnBD5NsF49y12BvhdBtDsYp/S8AAAAAAAAAACa30m84WaNutrRerqcS2a1s1j+uqy3kTkAAIA/AACAP5rNn7xchlE/Zn3hvAJ07r5jm2O9io2vPAAAAAAAAAAAmsL7PLsGgj+zXJQ9tHMFvwF4Vj024u28AAAAAAAAAACGVDE+2GKdP07VCj+zwii/Fb2bPiukXz4AAAAAAAAAAM0kBT24v6q7OpCUvK1/kjyQV0O9WnV3PQAAgD8AAIA/5hpiPT59tj9OAqQ+mlwjvr36rz0ihDw+AAAAAAAAAABNOq09q6omP0xIDD0GMtC+1F4BPoCPdb0AAAAAAAAAAGYSOL17cJC61hWuuwLyLTiDevo6Bni5tgAAgD8AAIA/Zmn+PLh1+rtb4wS+Vhjavc/1Wj3Wi7k+AACAPwAAgD/mCFm9roePup6us7YR0E4xr2ILuzBVzjUAAIA/AACAP81GojxsRv+7SMz8O3ppjjw0VVY9eqxuvQAAgD8AAIA/ZscjPqx1tD+igRk/UNWevvb9fT5Yn9w+AAAAAAAAAACtcGg+jQ6EP5h0Wz7aogK/Z+agPoWVO70AAAAAAAAAAM02JD1ca166w2hhNgBbQDFnJW+5FeeEtQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": -0.004566423357664329, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVNxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMImggbnp43ckCUhpRSlIwBbJRNBgGMAXSUR0CleidFfAsTdX2UKGgGaAloD0MIQ4zXvKr6cUCUhpRSlGgVS95oFkdApXo4bKifx3V9lChoBmgJaA9DCGAGY0RihHJAlIaUUpRoFUvwaBZHQKV6UuCf6Gh1fZQoaAZoCWgPQwiS5o9pbblxQJSGlFKUaBVL2WgWR0Clen6Kk2xZdX2UKGgGaAloD0MIxLEubqNubkCUhpRSlGgVS/ZoFkdApXp+RkmQbXV9lChoBmgJaA9DCJijx+8t2HBAlIaUUpRoFUvZaBZHQKV6lqN6w+t1fZQoaAZoCWgPQwh6Oey+I4BwQJSGlFKUaBVL+WgWR0Clep0O3DvWdX2UKGgGaAloD0MIELHBwgkbckCUhpRSlGgVTQkBaBZHQKV6rD63y7R1fZQoaAZoCWgPQwiI1/UL9mdxQJSGlFKUaBVL8mgWR0ClerMAeaKDdX2UKGgGaAloD0MIdy6M9CL8cECUhpRSlGgVS+poFkdApXr4YrJ8v3V9lChoBmgJaA9DCF/tKM4R/XJAlIaUUpRoFUvvaBZHQKV7VQmeDnN1fZQoaAZoCWgPQwj6eyk86MJwQJSGlFKUaBVL5WgWR0Cle21uJk5IdX2UKGgGaAloD0MI7E0MyUmNcECUhpRSlGgVS+toFkdApXw6dxyXD3V9lChoBmgJaA9DCG7ajNPQWnFAlIaUUpRoFUvYaBZHQKV8VBMSK3x1fZQoaAZoCWgPQwhpOGVuvjFxQJSGlFKUaBVLzWgWR0ClfGCz9jwydX2UKGgGaAloD0MI6+Oh7y4NdECUhpRSlGgVTQsBaBZHQKV8sl0HQhR1fZQoaAZoCWgPQwh2UInrmGxuQJSGlFKUaBVNAAFoFkdApXy2lImPYHV9lChoBmgJaA9DCHSV7q4zWm9AlIaUUpRoFUv8aBZHQKV85vDP4VR1fZQoaAZoCWgPQwg0Spf+JXpwQJSGlFKUaBVL82gWR0ClfPnIyTIOdX2UKGgGaAloD0MIf0+sU6UTcUCUhpRSlGgVS/doFkdApX0vWnTAnHV9lChoBmgJaA9DCOrsZHAUAW9AlIaUUpRoFUvnaBZHQKV9M5wwTM91fZQoaAZoCWgPQwj6tIr+0INyQJSGlFKUaBVL6mgWR0ClfUQFC9h7dX2UKGgGaAloD0MINxd/21ODcECUhpRSlGgVTQUBaBZHQKV9WNn5BTp1fZQoaAZoCWgPQwg2d/S/nMVxQJSGlFKUaBVNAgFoFkdApX1owPAfuHV9lChoBmgJaA9DCPWEJR5QCW9AlIaUUpRoFUvkaBZHQKV9iMtK7I11fZQoaAZoCWgPQwjHgOz1rppwQJSGlFKUaBVNHgFoFkdApX23UrkKeHV9lChoBmgJaA9DCJvIzAWu+3FAlIaUUpRoFUvsaBZHQKV+FLOiWVx1fZQoaAZoCWgPQwiEKjV7IKFwQJSGlFKUaBVNAgFoFkdApX40/pt78nV9lChoBmgJaA9DCM5Q3PGmZW9AlIaUUpRoFUv6aBZHQKV/GuKXOW11fZQoaAZoCWgPQwgSMpBnV7FxQJSGlFKUaBVL9WgWR0ClfzHGbTc7dX2UKGgGaAloD0MIW7VrQhpxcUCUhpRSlGgVS9toFkdApYjxJ04io3V9lChoBmgJaA9DCClauRfYA3JAlIaUUpRoFUvxaBZHQKWI8M4LkS51fZQoaAZoCWgPQwi0Hr5MlH9yQJSGlFKUaBVLzGgWR0CliPszVMEidX2UKGgGaAloD0MIjrJ+M/GBckCUhpRSlGgVS/doFkdApYkCVSn+AHV9lChoBmgJaA9DCKmJPh+l03BAlIaUUpRoFU0UAWgWR0CliQg4ffXPdX2UKGgGaAloD0MIH5+QnbcBc0CUhpRSlGgVS/BoFkdApYkhD5TIenV9lChoBmgJaA9DCPnzbcES7XBAlIaUUpRoFUvhaBZHQKWJOrMkhRt1fZQoaAZoCWgPQwhvS+SCMzBxQJSGlFKUaBVL4WgWR0CliUlUZNwjdX2UKGgGaAloD0MI7iHhe7/zcECUhpRSlGgVS9doFkdApYlRwVCXyHV9lChoBmgJaA9DCK/PnPUpO3FAlIaUUpRoFUvBaBZHQKWJZdpqREF1fZQoaAZoCWgPQwik42pkV8xwQJSGlFKUaBVL3WgWR0CliX2FN+LFdX2UKGgGaAloD0MI7nn+tBHtc0CUhpRSlGgVS/loFkdApYmR7NSqEXV9lChoBmgJaA9DCAgAjj27JnFAlIaUUpRoFUvKaBZHQKWJ72ki2Ul1fZQoaAZoCWgPQwiMEB5tHM1uQJSGlFKUaBVL4GgWR0CligbRnezldX2UKGgGaAloD0MI9RQ5RNyvcECUhpRSlGgVS9FoFkdApYq958jRlnV9lChoBmgJaA9DCD90QX0LInJAlIaUUpRoFUv0aBZHQKWLTP2wmmd1fZQoaAZoCWgPQwhaaOc0S0xwQJSGlFKUaBVL32gWR0Cli1cVYZEVdX2UKGgGaAloD0MIoBUYsvoVcECUhpRSlGgVS+ZoFkdApYt4ZdfLLnV9lChoBmgJaA9DCK3aNSGtTm9AlIaUUpRoFUvyaBZHQKWLkHyEtd11fZQoaAZoCWgPQwhW73A7NMRwQJSGlFKUaBVL+mgWR0Cli6h6jWTYdX2UKGgGaAloD0MIUmFsIchqcECUhpRSlGgVS/VoFkdApYv8O/cnE3V9lChoBmgJaA9DCFQ2rKlsGnNAlIaUUpRoFU0TAWgWR0CljBDNY8uBdX2UKGgGaAloD0MIuB6F61FpcUCUhpRSlGgVTQEBaBZHQKWMEqR2bG51fZQoaAZoCWgPQwiJCtXNBa5xQJSGlFKUaBVNDwFoFkdApYwgnlXA/XV9lChoBmgJaA9DCD60jxX8fm9AlIaUUpRoFUv9aBZHQKWMIl/H5rR1fZQoaAZoCWgPQwheY5eongpxQJSGlFKUaBVL8WgWR0CljDb/n4fwdX2UKGgGaAloD0MIZD+LpchhcUCUhpRSlGgVTRYBaBZHQKWMeR8twrF1fZQoaAZoCWgPQwh6AIv8OkFyQJSGlFKUaBVNBwFoFkdApYyEVclgMXV9lChoBmgJaA9DCG4yqgzjC3NAlIaUUpRoFUvxaBZHQKWMxbW3BpJ1fZQoaAZoCWgPQwj1nzU//iRzQJSGlFKUaBVNEQFoFkdApY0AyXUpeHV9lChoBmgJaA9DCIBmEB8YlXJAlIaUUpRoFUvUaBZHQKWNNvZRKpV1fZQoaAZoCWgPQwiEg72JISNRQJSGlFKUaBVLmmgWR0CljadzwMH9dX2UKGgGaAloD0MINUOqKB4vcECUhpRSlGgVS+toFkdApY3xvP1L8XV9lChoBmgJaA9DCEz9vKlItnFAlIaUUpRoFUvdaBZHQKWOAtnwob51fZQoaAZoCWgPQwgt7j8ynZhvQJSGlFKUaBVL+mgWR0Cljinc1wYMdX2UKGgGaAloD0MI7+apDrnocUCUhpRSlGgVS8poFkdApY5R6QeV9nV9lChoBmgJaA9DCFrXaDlQL25AlIaUUpRoFUvwaBZHQKWOVzbvgFZ1fZQoaAZoCWgPQwhdNGQ8ystxQJSGlFKUaBVNFQFoFkdApY6Yc/+sHXV9lChoBmgJaA9DCGHguffwdnFAlIaUUpRoFUvfaBZHQKWOqPq9oOB1fZQoaAZoCWgPQwh2wktwqoJxQJSGlFKUaBVL6WgWR0CljrFtj0+UdX2UKGgGaAloD0MIhWBVvfzGckCUhpRSlGgVS+VoFkdApY8Ci0v4/XV9lChoBmgJaA9DCHN/9bjvmXNAlIaUUpRoFUv3aBZHQKWPRLXcxj91fZQoaAZoCWgPQwjerMH7aiBxQJSGlFKUaBVNJgFoFkdApY9Q+0PYnXV9lChoBmgJaA9DCEpiSbl7tHBAlIaUUpRoFUvWaBZHQKWPc0jTrmh1fZQoaAZoCWgPQwjrVs9Jr95xQJSGlFKUaBVNAwFoFkdApY+tt65Xl3V9lChoBmgJaA9DCGZMwRqnqnJAlIaUUpRoFUvkaBZHQKWPzWDHwPR1fZQoaAZoCWgPQwgFTyFXqiZzQJSGlFKUaBVNdAFoFkdApZARqfvnbXV9lChoBmgJaA9DCGLcDaJ1xXNAlIaUUpRoFUveaBZHQKWQLL7Gecx1fZQoaAZoCWgPQwhGI59XvEtvQJSGlFKUaBVL1mgWR0ClkLctGus+dX2UKGgGaAloD0MI4LpiRvhJcUCUhpRSlGgVS/VoFkdApZDKyfL9uXV9lChoBmgJaA9DCCCaeXINu3BAlIaUUpRoFUv8aBZHQKWQ0AYpDu11fZQoaAZoCWgPQwjnb0IhgudyQJSGlFKUaBVLz2gWR0ClkOvKEFnqdX2UKGgGaAloD0MIfJqTFxkLcECUhpRSlGgVS9FoFkdApZFeh0yP/HV9lChoBmgJaA9DCHy3eeMkeHJAlIaUUpRoFUvzaBZHQKWRbTYukDZ1fZQoaAZoCWgPQwjC2a1l8odxQJSGlFKUaBVL/mgWR0ClkYczhxYJdX2UKGgGaAloD0MISGx3D1ARcUCUhpRSlGgVTS4BaBZHQKWRnGe+VTt1fZQoaAZoCWgPQwjBrFCkO1pzQJSGlFKUaBVNJgFoFkdApZGuLJjlP3V9lChoBmgJaA9DCEd3EDtT13FAlIaUUpRoFUvZaBZHQKWRuohpxm11fZQoaAZoCWgPQwjt153uPLhyQJSGlFKUaBVL1GgWR0ClkdjOC5EudX2UKGgGaAloD0MIf2q8dNPMcECUhpRSlGgVS/doFkdApZIVRaX8fnV9lChoBmgJaA9DCCjueJPfNlNAlIaUUpRoFUuoaBZHQKWSHKh+OOt1fZQoaAZoCWgPQwid8X1xKWBxQJSGlFKUaBVNAQFoFkdApZKPvOQhfXV9lChoBmgJaA9DCP2jb9L0XXBAlIaUUpRoFU0NAWgWR0ClktPK2a2GdX2UKGgGaAloD0MIQ5Hu51RSckCUhpRSlGgVS+loFkdApZOCXrt3OnV9lChoBmgJaA9DCJXXSuhuT3BAlIaUUpRoFUvraBZHQKWTqswL3K11fZQoaAZoCWgPQwifceFAyB1yQJSGlFKUaBVNOQFoFkdApZPCmGdqcnV9lChoBmgJaA9DCPZgUnx8EnBAlIaUUpRoFU0FAWgWR0Clk80UGmk4dX2UKGgGaAloD0MI8iVUcDhScECUhpRSlGgVTQ0BaBZHQKWT/QvYe1d1fZQoaAZoCWgPQwjK+ziaI8pxQJSGlFKUaBVL1WgWR0CllBGWldkbdX2UKGgGaAloD0MIe/ZcpiadckCUhpRSlGgVS+poFkdApZQqK3uuzXVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 584, "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-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:345ab0f8fc7bd1c628189f6abe6971d0aefa1687937d11e5249dec1c4f060d43
3
+ size 147122
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.2
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__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 ",
7
+ "__init__": "<function ActorCriticPolicy.__init__ at 0x7fd17d894ca0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd17d894d30>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd17d894dc0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd17d894e50>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fd17d894ee0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fd17d894f70>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd17d818040>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fd17d8180d0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd17d818160>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd17d8181f0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd17d818280>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fd17d8915d0>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {},
23
+ "observation_space": {
24
+ ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "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",
26
+ "dtype": "float32",
27
+ "_shape": [
28
+ 8
29
+ ],
30
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
31
+ "high": "[inf inf inf inf inf inf inf inf]",
32
+ "bounded_below": "[False False False False False False False False]",
33
+ "bounded_above": "[False False False False False False False False]",
34
+ "_np_random": null
35
+ },
36
+ "action_space": {
37
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
38
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 1376256,
46
+ "_total_timesteps": 1370000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1672428097806757523,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "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"
56
+ },
57
+ "_last_obs": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "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"
60
+ },
61
+ "_last_episode_starts": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
64
+ },
65
+ "_last_original_obs": null,
66
+ "_episode_num": 0,
67
+ "use_sde": false,
68
+ "sde_sample_freq": -1,
69
+ "_current_progress_remaining": -0.004566423357664329,
70
+ "ep_info_buffer": {
71
+ ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "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"
73
+ },
74
+ "ep_success_buffer": {
75
+ ":type:": "<class 'collections.deque'>",
76
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 584,
79
+ "n_steps": 1024,
80
+ "gamma": 0.999,
81
+ "gae_lambda": 0.98,
82
+ "ent_coef": 0.01,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 4,
87
+ "clip_range": {
88
+ ":type:": "<class 'function'>",
89
+ ":serialized:": "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"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5daff1cdab8863fd88c539c5fa777f7d2ba064262707ee220f9cdcf82f22b929
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1a21b189d859cc25ae8d2b28465c1cc8f26404792e4fd1181fd0faac26d97101
3
+ size 43201
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
2
+ Python: 3.8.16
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.13.0+cu116
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (190 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 268.90152354514396, "std_reward": 12.661240527098506, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-30T19:59:31.885894"}