pregonas commited on
Commit
8d369a1
·
1 Parent(s): ca41bac

Hugging FaceDRL Course Unit 1 LunarLander-v2

Browse files
.gitattributes CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
32
  *.zip filter=lfs diff=lfs merge=lfs -text
33
  *.zst filter=lfs diff=lfs merge=lfs -text
34
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
32
  *.zip filter=lfs diff=lfs merge=lfs -text
33
  *.zst filter=lfs diff=lfs merge=lfs -text
34
  *tfevents* filter=lfs diff=lfs merge=lfs -text
35
+ replay.mp4 filter=lfs diff=lfs merge=lfs -text
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: 247.11 +/- 21.03
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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f2d6ba145e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2d6ba14670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2d6ba14700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2d6ba14790>", "_build": "<function ActorCriticPolicy._build at 0x7f2d6ba14820>", "forward": "<function ActorCriticPolicy.forward at 0x7f2d6ba148b0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f2d6ba14940>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2d6ba149d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2d6ba14a60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2d6ba14af0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2d6ba14b80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2d6ba14c10>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2d6ba0d8a0>"}, "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": 8, "num_timesteps": 1007616, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677855746978269576, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQEAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAQAAAAAAAFo5cD608Yc/gh22PuUumL5PiJU+1WJovQAAAAAAAAAApq2fvaryNz+h8cM7Dap4vlddyzwdQta8AAAAAAAAAACa3yU8jytRvO6ajb0UVU88YOS2PTjcKL0AAIA/AACAP5pxcr3D5AE/umexPSU4lL7TYl09ksV4vAAAAAAAAAAA5niXvb453j6/+cU80yWavvoXnzxPNSs8AAAAAAAAAADNgJU8NPywP2+rGz+E/t2+FpCbvA5oy70AAAAAAAAAAICPS74lwpc/XqaQvhKLh74xN7W+GJ+rvAAAAAAAAAAAMHpYvkSQQT8uQxI+1F5kvv09S70kcho9AAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwhLCIaUjAFDlHSUUpQu"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.007616000000000067, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVfBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIZeHra137b0CUhpRSlIwBbJRNKwGMAXSUR0CVgPvf0mMPdX2UKGgGaAloD0MIumqeI/IXakCUhpRSlGgVTX0BaBZHQJWBwXdj5Kx1fZQoaAZoCWgPQwj8Ny9OfCVPQJSGlFKUaBVL+WgWR0CVgz7hNucddX2UKGgGaAloD0MIQ6uTM9R0cUCUhpRSlGgVTaoBaBZHQJWDSf29L6F1fZQoaAZoCWgPQwhrgT0mUgNyQJSGlFKUaBVNfwFoFkdAlZOrbpNbknV9lChoBmgJaA9DCI21v7O9u2xAlIaUUpRoFU07AWgWR0CVlOQgs9SudX2UKGgGaAloD0MI0v2cgvy4P0CUhpRSlGgVS/NoFkdAlZWQ4KhL5HV9lChoBmgJaA9DCEJ6ihyijW5AlIaUUpRoFU2XAWgWR0CVlkNkvsZ6dX2UKGgGaAloD0MIRBZp4h12cUCUhpRSlGgVTVMBaBZHQJWWRXXAdn11fZQoaAZoCWgPQwi+2HvxRSNAQJSGlFKUaBVL4GgWR0CVl8Szw+dLdX2UKGgGaAloD0MITWn9LcFVcUCUhpRSlGgVTU0BaBZHQJWYU88s+V11fZQoaAZoCWgPQwilhGBVvaVwQJSGlFKUaBVNSAFoFkdAlZnBV+7UX3V9lChoBmgJaA9DCOnvpfAg0W5AlIaUUpRoFU13AWgWR0CVnEbbUPQOdX2UKGgGaAloD0MIBWnGoil/cUCUhpRSlGgVTVcBaBZHQJWcYOavzOJ1fZQoaAZoCWgPQwhbRBSTdyBwQJSGlFKUaBVNZAFoFkdAlZ0YwZflZHV9lChoBmgJaA9DCPbuj/eqwG9AlIaUUpRoFU1aAWgWR0CVnWknTiKjdX2UKGgGaAloD0MIti41Qr8tbkCUhpRSlGgVTakBaBZHQJWfDho/Rmd1fZQoaAZoCWgPQwisPIGw00puQJSGlFKUaBVNkAFoFkdAlaA6DsdDIHV9lChoBmgJaA9DCIfhI2LKY2tAlIaUUpRoFU16AWgWR0CVoFk+HJtBdX2UKGgGaAloD0MIhugQOBJ2cUCUhpRSlGgVTVwBaBZHQJWhMxtYSxt1fZQoaAZoCWgPQwh8uU+OAihGwJSGlFKUaBVNAAFoFkdAlaKTFMqSYHV9lChoBmgJaA9DCHztmSWB93FAlIaUUpRoFU05AWgWR0CVoq1b7j1gdX2UKGgGaAloD0MI6iRbXc4Rb0CUhpRSlGgVTT0BaBZHQJWi0wWWQfZ1fZQoaAZoCWgPQwizCMVWUO1vQJSGlFKUaBVNRwFoFkdAlaOTmnwXqXV9lChoBmgJaA9DCOCFrdnKu3BAlIaUUpRoFU1rAWgWR0CVph84gieNdX2UKGgGaAloD0MIt0WZDbIca0CUhpRSlGgVTUMBaBZHQJWp9DneSB91fZQoaAZoCWgPQwiq86j4P/1sQJSGlFKUaBVNyAFoFkdAlao8er+5v3V9lChoBmgJaA9DCIVCBBxCG3FAlIaUUpRoFU1DAWgWR0CVqlaB7NSqdX2UKGgGaAloD0MInff/cYIVcECUhpRSlGgVTVYBaBZHQJW0pN1yNn51fZQoaAZoCWgPQwjiAWVTrnFwQJSGlFKUaBVN5wFoFkdAlbYYjW07bXV9lChoBmgJaA9DCMB2MGKfgXBAlIaUUpRoFU11AWgWR0CVtlWjXWe6dX2UKGgGaAloD0MIA3l2+dbLb0CUhpRSlGgVTT4BaBZHQJW3dtygf2d1fZQoaAZoCWgPQwhLkBFQ4eRwQJSGlFKUaBVNugJoFkdAlbjWIXTEznV9lChoBmgJaA9DCNzawvPS/mxAlIaUUpRoFU1fAWgWR0CVuvahpQDWdX2UKGgGaAloD0MIO/w1WaMGb0CUhpRSlGgVTUsBaBZHQJW7DW5H3Dh1fZQoaAZoCWgPQwjj4qjcBEFyQJSGlFKUaBVNZgFoFkdAlbtJA6dUbXV9lChoBmgJaA9DCAdCsoAJuWtAlIaUUpRoFU1qAWgWR0CVu297WuoxdX2UKGgGaAloD0MI41KVtrircECUhpRSlGgVTTcBaBZHQJW8FvXK8th1fZQoaAZoCWgPQwinXOFdLgtyQJSGlFKUaBVNuwFoFkdAlb5l2vB7/nV9lChoBmgJaA9DCBzRPeva0HBAlIaUUpRoFU1pAWgWR0CVvoEovzvrdX2UKGgGaAloD0MIHqM883KGbECUhpRSlGgVTV4BaBZHQJXAb2/SH/N1fZQoaAZoCWgPQwietkYE40FvQJSGlFKUaBVNHAFoFkdAlcHPqoqCpXV9lChoBmgJaA9DCCqoqPoVa3BAlIaUUpRoFU2FAWgWR0CVxNrnkkrxdX2UKGgGaAloD0MIJET5gpZGbECUhpRSlGgVTYIBaBZHQJXE5Q1rIo51fZQoaAZoCWgPQwgAxciSOWJxQJSGlFKUaBVNTQFoFkdAlcUuE/Spi3V9lChoBmgJaA9DCNfBwd4EC3BAlIaUUpRoFU2EAWgWR0CVxXlLOAy3dX2UKGgGaAloD0MIFvn1Q+yVbkCUhpRSlGgVTVIBaBZHQJXIar5qM3t1fZQoaAZoCWgPQwgb9KW3f85xQJSGlFKUaBVNfAFoFkdAlcyeoLofS3V9lChoBmgJaA9DCG/XS1OE125AlIaUUpRoFU3lAWgWR0CVzk1k1/DtdX2UKGgGaAloD0MIJAnCFdBCcUCUhpRSlGgVTUMBaBZHQJXaluLrHEN1fZQoaAZoCWgPQwiqtpvgG1hvQJSGlFKUaBVNngFoFkdAldqe4Cp3o3V9lChoBmgJaA9DCMyYgjVOemxAlIaUUpRoFU1FAWgWR0CV2tQEIPbxdX2UKGgGaAloD0MIgez17g+qcECUhpRSlGgVTUYBaBZHQJXbDPKMefZ1fZQoaAZoCWgPQwgNjpJX5xBxQJSGlFKUaBVNhwFoFkdAldu69bor4HV9lChoBmgJaA9DCOxOd544BXNAlIaUUpRoFU1jAWgWR0CV3WiF0xM4dX2UKGgGaAloD0MIYadYNUifckCUhpRSlGgVTXIBaBZHQJXgRswco6V1fZQoaAZoCWgPQwg983LYve1xQJSGlFKUaBVNKQFoFkdAleBovzvqknV9lChoBmgJaA9DCFitTPjli3FAlIaUUpRoFU12AWgWR0CV4WgW8AaOdX2UKGgGaAloD0MIvW4RGCtXcECUhpRSlGgVTTgBaBZHQJXhaiAUcn51fZQoaAZoCWgPQwiYwRiRqDptQJSGlFKUaBVNjAFoFkdAleK6c/dIoXV9lChoBmgJaA9DCE3Z6Qf1DW1AlIaUUpRoFU1OAWgWR0CV4tOJcgQpdX2UKGgGaAloD0MI/irAd9ulcUCUhpRSlGgVTY8BaBZHQJXi/cRDkU91fZQoaAZoCWgPQwibx2Ewv2xwQJSGlFKUaBVNUwFoFkdAleR1Vo6CDnV9lChoBmgJaA9DCCZWRiOf10RAlIaUUpRoFUvvaBZHQJXnk+bExZd1fZQoaAZoCWgPQwg91/fhoF9uQJSGlFKUaBVNYgFoFkdAleeg5Jbt7nV9lChoBmgJaA9DCA7Xag/7wnBAlIaUUpRoFU1GAWgWR0CV5+S7oStedX2UKGgGaAloD0MItWtCWqMyckCUhpRSlGgVTXsBaBZHQJXoGwSrYGt1fZQoaAZoCWgPQwhm+iXirRtxQJSGlFKUaBVNXQFoFkdAlehgKSgXdnV9lChoBmgJaA9DCMZvCitVZnBAlIaUUpRoFU1lAWgWR0CV6a6Ae7tidX2UKGgGaAloD0MI+tAF9a0jcECUhpRSlGgVTekBaBZHQJXsjcTJyQx1fZQoaAZoCWgPQwh3EaYoF7lwQJSGlFKUaBVNiQFoFkdAley/tpmEoXV9lChoBmgJaA9DCMl3KXUJiXJAlIaUUpRoFU0sAWgWR0CV7evAXVLBdX2UKGgGaAloD0MINBKhEWzNbUCUhpRSlGgVTUEBaBZHQJXu4lyBCld1fZQoaAZoCWgPQwjOUNzxpitvQJSGlFKUaBVNWwFoFkdAle76KLsKLXV9lChoBmgJaA9DCHv3x3tVAG1AlIaUUpRoFU1UAWgWR0CV+Sy6tknUdX2UKGgGaAloD0MIU3jQ7Hr9cUCUhpRSlGgVTVkBaBZHQJX5oqDsdDJ1fZQoaAZoCWgPQwjUtmEURKpwQJSGlFKUaBVNJAFoFkdAlfnUvCdjG3V9lChoBmgJaA9DCLcos0GmknBAlIaUUpRoFU0/AWgWR0CV/ceCCjDbdX2UKGgGaAloD0MIKnKIuDmScUCUhpRSlGgVTU8BaBZHQJX+BLAYYSB1fZQoaAZoCWgPQwiVgJiEy7JxQJSGlFKUaBVNOwFoFkdAlf9Q3PzFuXV9lChoBmgJaA9DCOXVOQZkr+a/lIaUUpRoFU0EAWgWR0CWAIPacqe9dX2UKGgGaAloD0MIxqUqbXFJb0CUhpRSlGgVTTgBaBZHQJYApZs9B8h1fZQoaAZoCWgPQwghWivaHB1uQJSGlFKUaBVNQwFoFkdAlgEd0V8CxXV9lChoBmgJaA9DCPazWIrkpG1AlIaUUpRoFU1/AWgWR0CWAnCeEqUedX2UKGgGaAloD0MIqu/8ooTTbkCUhpRSlGgVTZkBaBZHQJYEJOGj9GZ1fZQoaAZoCWgPQwiZR/5gIPBxQJSGlFKUaBVNNAFoFkdAlgawO8TSLXV9lChoBmgJaA9DCJFgqpk1im5AlIaUUpRoFU1EAWgWR0CWB3nogV45dX2UKGgGaAloD0MIJh3lYDZ4bUCUhpRSlGgVTUQBaBZHQJYIzqB3A211fZQoaAZoCWgPQwhIF5tWyvtwQJSGlFKUaBVNNgFoFkdAlgmSBoVVP3V9lChoBmgJaA9DCAFuFi9W8HBAlIaUUpRoFU1XAWgWR0CWCrYRdyDJdX2UKGgGaAloD0MIgQUwZWC2cECUhpRSlGgVTSkBaBZHQJYLVsP8Q7N1fZQoaAZoCWgPQwhW73A7tPdvQJSGlFKUaBVNdQFoFkdAlgwJuyeI23V9lChoBmgJaA9DCOY7+IlDDXFAlIaUUpRoFU1IAWgWR0CWDd+F10T2dX2UKGgGaAloD0MI/pyC/OzUbkCUhpRSlGgVTVcBaBZHQJYQT0rbxmV1fZQoaAZoCWgPQwiB6EmZ1PpsQJSGlFKUaBVNRgFoFkdAlhB4hMajvnV9lChoBmgJaA9DCCP5SiDlG3FAlIaUUpRoFU0oAWgWR0CWELTER8MNdX2UKGgGaAloD0MIHsL4adyTN0CUhpRSlGgVS/toFkdAlhFnV09yLnV9lChoBmgJaA9DCLXBiehXem9AlIaUUpRoFU1pAWgWR0CWEnOLiuMddX2UKGgGaAloD0MI++b+6rGPckCUhpRSlGgVTUkBaBZHQJYSjJ1aGHp1fZQoaAZoCWgPQwjyBwPPPcZuQJSGlFKUaBVNRAFoFkdAlhNHUH6dlXVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 492, "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-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "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:d83d20cabb6069904e274235eec30bc2f8d631be397c8d52a286e2bd9328333e
3
+ size 147063
ppo_LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
ppo_LunarLander-v2/data ADDED
@@ -0,0 +1,95 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f2d6ba145e0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2d6ba14670>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2d6ba14700>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2d6ba14790>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f2d6ba14820>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f2d6ba148b0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f2d6ba14940>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2d6ba149d0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f2d6ba14a60>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2d6ba14af0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2d6ba14b80>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2d6ba14c10>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f2d6ba0d8a0>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "observation_space": {
25
+ ":type:": "<class 'gym.spaces.box.Box'>",
26
+ ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
27
+ "dtype": "float32",
28
+ "_shape": [
29
+ 8
30
+ ],
31
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
32
+ "high": "[inf inf inf inf inf inf inf inf]",
33
+ "bounded_below": "[False False False False False False False False]",
34
+ "bounded_above": "[False False False False False False False False]",
35
+ "_np_random": null
36
+ },
37
+ "action_space": {
38
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
39
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
40
+ "n": 4,
41
+ "_shape": [],
42
+ "dtype": "int64",
43
+ "_np_random": null
44
+ },
45
+ "n_envs": 8,
46
+ "num_timesteps": 1007616,
47
+ "_total_timesteps": 1000000,
48
+ "_num_timesteps_at_start": 0,
49
+ "seed": null,
50
+ "action_noise": null,
51
+ "start_time": 1677855746978269576,
52
+ "learning_rate": 0.0003,
53
+ "tensorboard_log": null,
54
+ "lr_schedule": {
55
+ ":type:": "<class 'function'>",
56
+ ":serialized:": "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"
57
+ },
58
+ "_last_obs": {
59
+ ":type:": "<class 'numpy.ndarray'>",
60
+ ":serialized:": "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"
61
+ },
62
+ "_last_episode_starts": {
63
+ ":type:": "<class 'numpy.ndarray'>",
64
+ ":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="
65
+ },
66
+ "_last_original_obs": null,
67
+ "_episode_num": 0,
68
+ "use_sde": false,
69
+ "sde_sample_freq": -1,
70
+ "_current_progress_remaining": -0.007616000000000067,
71
+ "ep_info_buffer": {
72
+ ":type:": "<class 'collections.deque'>",
73
+ ":serialized:": "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"
74
+ },
75
+ "ep_success_buffer": {
76
+ ":type:": "<class 'collections.deque'>",
77
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
78
+ },
79
+ "_n_updates": 492,
80
+ "n_steps": 1024,
81
+ "gamma": 0.999,
82
+ "gae_lambda": 0.98,
83
+ "ent_coef": 0.01,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 4,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "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"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null
95
+ }
ppo_LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:469920a66a36f789d4b5074d34ac89e77f2a2169d4c836ddcb04cf2c0a176594
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:f3bf19044606580e9f78486e6db7e0323a1e00475a37f1b69d8ff165ca8f7b70
3
+ size 43393
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-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.10
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Gym: 0.21.0
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7d01b1e5ebf670940f2b805ce03de06ada0d9009ba2d19d6cae771560dcc02f9
3
+ size 1616994
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 247.11107300000003, "std_reward": 21.026613760054087, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-03T15:55:45.041509"}