vitorhgomes commited on
Commit
a64ac6b
1 Parent(s): dfe1bdc

Testing PPO on LunarLander-v2 environment

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: 267.67 +/- 21.66
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 0x7f54806f7160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f54806f71f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f54806f7280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f54806f7310>", "_build": "<function ActorCriticPolicy._build at 0x7f54806f73a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f54806f7430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f54806f74c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f54806f7550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f54806f75e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f54806f7670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f54806f7700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f54806f15d0>"}, "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": 1015808, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670363676578393420, "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:": "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"}, "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": "3.8.15", "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 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:66e4fa4b5f4162d4a187f9dc9c2ea3742a04030a0889e855c3aa652eb1e6e4de
3
+ size 147156
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 0x7f54806f7160>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f54806f71f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f54806f7280>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f54806f7310>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f54806f73a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f54806f7430>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f54806f74c0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f54806f7550>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f54806f75e0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f54806f7670>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f54806f7700>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f54806f15d0>"
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": 1000000.0,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1670363676578393420,
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:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAE2MeT0ZQI8/RUbOPbB0n75ceqE9fvwlPQAAAAAAAAAAzXyAvHRUkz1CHgG8MgQevnHliL0xRoc9AAAAAAAAAADA+KI9pNwWu3RfgLwyW4k8TqK0vGDBbD0AAIA/AACAPwDOXb0kJNc9kgFVPsbjb75KOwq9QsmfPAAAAAAAAAAAZlJuPdf/Xz+ug9y7G0F0vlK2zLtG9M45AAAAAAAAAACFuLG+/uK1PnM1uz56PXO+UzTHvHt6Tz4AAAAAAAAAANr1bj4Bgta8iVmfPGWiAbsj4US+fBPHuwAAgD8AAIA/syCnPUFqhj5kj5W97OVvvpB/57xjCpM9AAAAAAAAAADmPcU90ssAPgXyhz0242S+2O0fOyJ/Aj0AAAAAAAAAAGaceTyHmRk+YCoSvisRcr7q4pC9tLADPQAAAAAAAAAAQAmnPRT8m7pX3y200QOGrXrbkbpCLrAzAACAPwAAgD8gshQ+jpGYPgGniL7XUpK+fa6FvVJZ2jwAAAAAAAAAAGZlfL2YnNI+Xs4aPoOic75ky5e7BvsRPQAAAAAAAAAA+geWPocYdD8Wq3Q7bt23voVoZz4w4e+9AAAAAAAAAADmIT094Kq8PhSrGzwWdFm+33z3OmI7Ir0AAAAAAAAAAM3ngzxcny265SJuNRrxDS9q6YM7sJawtAAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
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 sha256:5b46bdc3a6b8915e76e1662cae6180d37de688dabc3257f74fc3a6d3d25aca69
3
+ size 87865
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cb0d521f2a73c3733cd3b14b162a0105a278b44be29709b1f78289b845858a09
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: 3.8.15
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.12.1+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (227 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 267.67226201620747, "std_reward": 21.65784185282452, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-06T22:20:01.652757"}