wooihen commited on
Commit
8bdaf21
·
1 Parent(s): f35201b

Upload PPO LunarLander-v2 trained agent

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: 262.79 +/- 27.06
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 0x7f0914dd0af0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0914dd0b80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0914dd0c10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0914dd0ca0>", "_build": "<function ActorCriticPolicy._build at 0x7f0914dd0d30>", "forward": "<function ActorCriticPolicy.forward at 0x7f0914dd0dc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0914dd0e50>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0914dd0ee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0914dd0f70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0914dd5040>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0914dd50d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0914dcd420>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671118544011202146, "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:": "gAWVdBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIM25qoHkCcUCUhpRSlIwBbJRNQQGMAXSUR0CeVzngYP5IdX2UKGgGaAloD0MIoUyjyYX1cUCUhpRSlGgVTQ0BaBZHQJ5YPPWxyGV1fZQoaAZoCWgPQwi7KeW10lRwQJSGlFKUaBVNQAJoFkdAnlhRsImgJ3V9lChoBmgJaA9DCPM7TWY8cW9AlIaUUpRoFU0yAWgWR0CeWKjW07bMdX2UKGgGaAloD0MI0erkDAVScECUhpRSlGgVTa4BaBZHQJ5Y7S6UaAF1fZQoaAZoCWgPQwhgyVUsPp1xQJSGlFKUaBVNCgFoFkdAnlmhqCYkV3V9lChoBmgJaA9DCH1bsFQX22xAlIaUUpRoFU1FAWgWR0CeW5ahpQDWdX2UKGgGaAloD0MI66hqgigKckCUhpRSlGgVTWsBaBZHQJ5dZMHryDt1fZQoaAZoCWgPQwgofSHkfIdwQJSGlFKUaBVL9mgWR0CeXa9XLeQ/dX2UKGgGaAloD0MIZFxxcZTpcUCUhpRSlGgVTQkBaBZHQJ5d9TOxB3R1fZQoaAZoCWgPQwjjcOZX89BtQJSGlFKUaBVNNAFoFkdAnl4+RYA80XV9lChoBmgJaA9DCApmTMHaiXJAlIaUUpRoFU0yAWgWR0CeX1baAWi2dX2UKGgGaAloD0MIJc/1fbi/b0CUhpRSlGgVTQIBaBZHQJ5fbNGEwnJ1fZQoaAZoCWgPQwiOkewRalNvQJSGlFKUaBVNLgFoFkdAnl/Gnn+yaHV9lChoBmgJaA9DCPUUOURc/m9AlIaUUpRoFU0hAWgWR0CeYHETg2qDdX2UKGgGaAloD0MIhdBBl7ADcUCUhpRSlGgVTQwBaBZHQJ5hFZEDyOJ1fZQoaAZoCWgPQwjC+dSxStJvQJSGlFKUaBVNRAFoFkdAnmETqKP4mHV9lChoBmgJaA9DCEG4Agq1/3BAlIaUUpRoFU0OAWgWR0CeYYL876pHdX2UKGgGaAloD0MIBWoxeFjAcECUhpRSlGgVTSkBaBZHQJ5h5UDMeOp1fZQoaAZoCWgPQwh3SDFAYoVyQJSGlFKUaBVL/2gWR0CeYkn9vS+hdX2UKGgGaAloD0MImYOgo1UCcECUhpRSlGgVTeQBaBZHQJ5jtUaQ3gl1fZQoaAZoCWgPQwiLa3wme0ptQJSGlFKUaBVNXgFoFkdAnmQ+ctoSMHV9lChoBmgJaA9DCLUaEvfYgm1AlIaUUpRoFU0wAWgWR0CeZcaX8fmtdX2UKGgGaAloD0MIG2X9ZqIYcUCUhpRSlGgVTRwBaBZHQJ5mx3IMjNZ1fZQoaAZoCWgPQwg+eViotVJsQJSGlFKUaBVNAgFoFkdAnmd6ZQYUFnV9lChoBmgJaA9DCMdl3NRAFXJAlIaUUpRoFU0EAWgWR0CeZ5zcAR02dX2UKGgGaAloD0MI8bc9QeIgbECUhpRSlGgVTTABaBZHQJ5oFGus90R1fZQoaAZoCWgPQwgLem8MQaBxQJSGlFKUaBVNRwFoFkdAnmhgEMb3oXV9lChoBmgJaA9DCFFn7iEhL3FAlIaUUpRoFU1BAWgWR0CeaF2sJY1YdX2UKGgGaAloD0MINPeQ8D37cECUhpRSlGgVTRABaBZHQJ5pVfZ26kJ1fZQoaAZoCWgPQwgj9Z7KqfxwQJSGlFKUaBVNPwFoFkdAnmmh59mYjXV9lChoBmgJaA9DCJdXrrfNg3JAlIaUUpRoFU0CAWgWR0CeabZ7HAARdX2UKGgGaAloD0MIYOl8eFaGcUCUhpRSlGgVTRgBaBZHQJ5p9HiFTNt1fZQoaAZoCWgPQwi4dTdPddxuQJSGlFKUaBVNUQFoFkdAnmqY7q6e5HV9lChoBmgJaA9DCEhqoWRye29AlIaUUpRoFU0xAWgWR0Cea1DWK/EgdX2UKGgGaAloD0MI1ZelnRqXcUCUhpRSlGgVTRIBaBZHQJ5rtyYG+sZ1fZQoaAZoCWgPQwj44ov2eN1OQJSGlFKUaBVL12gWR0CebAwiaAnVdX2UKGgGaAloD0MIOBH92rpickCUhpRSlGgVTYwBaBZHQJ5srSLIgeR1fZQoaAZoCWgPQwjds67RcmpwQJSGlFKUaBVNLAFoFkdAnmzvAj6eoXV9lChoBmgJaA9DCNoc5zYh8XFAlIaUUpRoFUvfaBZHQJ5tFowmE5B1fZQoaAZoCWgPQwiH3Aw34I9xQJSGlFKUaBVL+GgWR0CebndZJTVEdX2UKGgGaAloD0MIprbUQV7JcECUhpRSlGgVS/loFkdAnm9B6Ww/xHV9lChoBmgJaA9DCOZAD7VtXm1AlIaUUpRoFU0gAWgWR0Ceb5r3TNMXdX2UKGgGaAloD0MIN23GaYiZckCUhpRSlGgVTSABaBZHQJ5wJpCa7Vd1fZQoaAZoCWgPQwit3XahudZxQJSGlFKUaBVNFwFoFkdAnnAqqXF98nV9lChoBmgJaA9DCCkmb4AZeHNAlIaUUpRoFUv2aBZHQJ5wMiA2AG11fZQoaAZoCWgPQwjA6siRTiRuQJSGlFKUaBVNGQFoFkdAnnGpTQ3PzHV9lChoBmgJaA9DCLVQMjn1dHFAlIaUUpRoFUvoaBZHQJ5y9R/EwWZ1fZQoaAZoCWgPQwhy3CkdrK5wQJSGlFKUaBVNBgFoFkdAnnOTBMzuW3V9lChoBmgJaA9DCHUF24inRnFAlIaUUpRoFU08AWgWR0Cec/9QoCuEdX2UKGgGaAloD0MIzNQkeMPxakCUhpRSlGgVTSoBaBZHQJ50RALRa5h1fZQoaAZoCWgPQwhQGmoU0pZxQJSGlFKUaBVL+2gWR0CedGo+fRNRdX2UKGgGaAloD0MIJoqQuh0DcECUhpRSlGgVTYMBaBZHQJ6Jt3np0Op1fZQoaAZoCWgPQwitMlNaP2VxQJSGlFKUaBVNTAFoFkdAnovHZsbednV9lChoBmgJaA9DCLfRAN6CIHBAlIaUUpRoFU1kAWgWR0CejO/dZaFFdX2UKGgGaAloD0MIMCk+PqHxckCUhpRSlGgVTRMBaBZHQJ6NKwNb1RN1fZQoaAZoCWgPQwgZBFYOrWJyQJSGlFKUaBVNDwFoFkdAno2wm/nGKnV9lChoBmgJaA9DCMsuGFzzDG5AlIaUUpRoFU1MAWgWR0Ceje6rNnoQdX2UKGgGaAloD0MIBAKdSZuacUCUhpRSlGgVTSMBaBZHQJ6OcXXRPXV1fZQoaAZoCWgPQwg89rNYCkdwQJSGlFKUaBVNdwFoFkdAnpBG0qpcX3V9lChoBmgJaA9DCPFJJxKMFnNAlIaUUpRoFU0MAWgWR0CekKS5y2hJdX2UKGgGaAloD0MIt9PWiODMbECUhpRSlGgVTXcBaBZHQJ6RVfv4M4N1fZQoaAZoCWgPQwilgoqqn0lxQJSGlFKUaBVNAAFoFkdAnpGOivgWJ3V9lChoBmgJaA9DCJjbvdwnlXFAlIaUUpRoFU1KAWgWR0CelAGvwEyMdX2UKGgGaAloD0MIZoS3B6HQcECUhpRSlGgVTWcBaBZHQJ6UsdjoZAJ1fZQoaAZoCWgPQwip91ROO3VwQJSGlFKUaBVNWQFoFkdAnpUZ8neBQXV9lChoBmgJaA9DCJwyN9+IJmRAlIaUUpRoFU3JAmgWR0CelS/Aj6eodX2UKGgGaAloD0MIHv0v1yItckCUhpRSlGgVTcwBaBZHQJ6WKQNkOI91fZQoaAZoCWgPQwiuEiwOZ/BxQJSGlFKUaBVNJAFoFkdAnpZFJYkmhXV9lChoBmgJaA9DCNlcNc+RenFAlIaUUpRoFU0AAWgWR0CelkFFlTWHdX2UKGgGaAloD0MIZJC7CJNWcECUhpRSlGgVTV4BaBZHQJ6WVdt2s7x1fZQoaAZoCWgPQwgf9dcrLIFtQJSGlFKUaBVNAAFoFkdAnpajNMXaanV9lChoBmgJaA9DCHqlLEPcBXJAlIaUUpRoFU1RAWgWR0CemFxH5JsgdX2UKGgGaAloD0MIzNB4IojAb0CUhpRSlGgVTSgBaBZHQJ6YYYNy5qd1fZQoaAZoCWgPQwgMWd3quSxuQJSGlFKUaBVNSQFoFkdAnpjgB1cMVnV9lChoBmgJaA9DCLiRskXS2HFAlIaUUpRoFU0KAWgWR0CemhmtyPuHdX2UKGgGaAloD0MI5Eo9C4KqcUCUhpRSlGgVTTABaBZHQJ6aKnEVFhJ1fZQoaAZoCWgPQwgqApzeRRxtQJSGlFKUaBVNKgFoFkdAnppM2rGR3nV9lChoBmgJaA9DCOSfGcSHOHJAlIaUUpRoFU0DAWgWR0CenJGetjkNdX2UKGgGaAloD0MIq0IDsWyRbkCUhpRSlGgVTV8BaBZHQJ6cq/RE4Nt1fZQoaAZoCWgPQwhwtOOG35NvQJSGlFKUaBVNNwFoFkdAnp3PtdAxBXV9lChoBmgJaA9DCLVug9qvMnNAlIaUUpRoFU0pAWgWR0Cenk0BwMpgdX2UKGgGaAloD0MICf1Mve57ckCUhpRSlGgVTSwBaBZHQJ6fydYnv2J1fZQoaAZoCWgPQwhU/yCSIStuQJSGlFKUaBVNNAFoFkdAnqAymqHXVnV9lChoBmgJaA9DCAIQd/WqA29AlIaUUpRoFU1BAWgWR0CeoJcM3IdVdX2UKGgGaAloD0MIA9GTMikQcECUhpRSlGgVS/9oFkdAnqDvmozeoHV9lChoBmgJaA9DCEp9WdrpZ3BAlIaUUpRoFU13AWgWR0CeoUhxYJVsdX2UKGgGaAloD0MInDOitPeKcUCUhpRSlGgVTVkBaBZHQJ6h11yNn5B1fZQoaAZoCWgPQwixbycRodVyQJSGlFKUaBVL92gWR0CeooN5MURGdX2UKGgGaAloD0MISmHe48whckCUhpRSlGgVTY0BaBZHQJ6i2g7HQyB1fZQoaAZoCWgPQwh2+kFdpIlvQJSGlFKUaBVNEAFoFkdAnqN8HryDqXV9lChoBmgJaA9DCOl/uRZtq3FAlIaUUpRoFU1KAWgWR0Ceo8uIAOridX2UKGgGaAloD0MITiUDQBUccUCUhpRSlGgVTXoBaBZHQJ6ktPuXu3N1fZQoaAZoCWgPQwhjDoKOVidvQJSGlFKUaBVNEAFoFkdAnqWtU0elsXV9lChoBmgJaA9DCFqAttVs1HJAlIaUUpRoFU0dAWgWR0CepfpYLb5/dX2UKGgGaAloD0MIKA6g33eCcUCUhpRSlGgVTQEBaBZHQJ6mnyLAHml1fZQoaAZoCWgPQwguWKoL+C9yQJSGlFKUaBVL+WgWR0Cep6VJtix3dX2UKGgGaAloD0MInmLVIMwqcUCUhpRSlGgVS/VoFkdAnqfXBtUGV3V9lChoBmgJaA9DCE91yM2wunJAlIaUUpRoFU1QAWgWR0CeqKvgWJrMdX2UKGgGaAloD0MIjh6/tymPcECUhpRSlGgVTRYBaBZHQJ6p4RnOB191ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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 sha256:53798a2ad3a211a58e5a3762f0fef115ad7dd0dfd95a2fba002883061d2f66f9
3
+ size 147202
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 0x7f0914dd0af0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0914dd0b80>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0914dd0c10>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0914dd0ca0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f0914dd0d30>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f0914dd0dc0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0914dd0e50>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f0914dd0ee0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0914dd0f70>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0914dd5040>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0914dd50d0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f0914dcd420>"
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": 1015808,
46
+ "_total_timesteps": 1000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1671118544011202146,
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": -0.015808000000000044,
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": 248,
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 sha256:23566e44bcbde4b6ee64854dcb959c6fb41342611ef1a0fdcac0040d5b173a1b
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:ce0d40f3c79d0eb2d79820a38d0a4b5d3a9f05b715151823ae1c74210987df22
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 (198 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 262.7949035132016, "std_reward": 27.058775493489794, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-15T15:59:51.876631"}