Chris1 commited on
Commit
f678755
1 Parent(s): af7ccf4

Upload PPO LunarLander-v2 trained agent

Browse files
.gitattributes CHANGED
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
28
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ - metrics:
12
+ - type: mean_reward
13
+ value: 166.92 +/- 97.85
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: LunarLander-v2
20
+ type: LunarLander-v2
21
+ ---
22
+
23
+ # **PPO** Agent playing **LunarLander-v2**
24
+ This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
25
+
26
+ ## Usage (with Stable-baselines3)
27
+ TODO: Add your code
28
+
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 0x7fac046f3ee0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fac046f3f70>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fac046f7040>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fac046f70d0>", "_build": "<function ActorCriticPolicy._build at 0x7fac046f7160>", "forward": "<function ActorCriticPolicy.forward at 0x7fac046f71f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fac046f7280>", "_predict": "<function ActorCriticPolicy._predict at 0x7fac046f7310>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fac046f73a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fac046f7430>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fac046f74c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fac046ee900>"}, "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": 524288, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652914591.7088978, "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": -0.04857599999999995, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 160, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.13.0-41-generic-x86_64-with-glibc2.29 #46~20.04.1-Ubuntu SMP Wed Apr 20 13:16:21 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.22.3", "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:cd3f3f654ae59989827e85a6f71f9fd148bd4e40d65e764a4c21cf127c6e77b1
3
+ size 144029
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.0
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 0x7fac046f3ee0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fac046f3f70>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fac046f7040>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fac046f70d0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fac046f7160>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fac046f71f0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fac046f7280>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fac046f7310>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fac046f73a0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fac046f7430>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fac046f74c0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fac046ee900>"
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": 524288,
46
+ "_total_timesteps": 500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1652914591.7088978,
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": -0.04857599999999995,
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": 160,
79
+ "n_steps": 2048,
80
+ "gamma": 0.99,
81
+ "gae_lambda": 0.95,
82
+ "ent_coef": 0.0,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 10,
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:c4a88a8de3ec4af3fc2c3f77e455ebe8c62dfd2ca3d1cfb057ea04c154412b29
3
+ size 84893
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:85989670bdede92650ba0f25b6f54b7cad62bac8a1fd0b4bbe4a56f6d70b5cc2
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-5.13.0-41-generic-x86_64-with-glibc2.29 #46~20.04.1-Ubuntu SMP Wed Apr 20 13:16:21 UTC 2022
2
+ Python: 3.8.10
3
+ Stable-Baselines3: 1.5.0
4
+ PyTorch: 1.11.0+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.22.3
7
+ Gym: 0.21.0
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6e62a4798529fd6c24eb4fe101e90200e75f0c6d982e90dee426cb95619ce73a
3
+ size 246562
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 166.9206272354349, "std_reward": 97.84850146273789, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-19T01:23:49.115102"}