Alex-yang commited on
Commit
c3c23c8
1 Parent(s): 214cad6

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: 215.57 +/- 27.04
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 0x7fa20e130f80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa20e156050>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa20e1560e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa20e156170>", "_build": "<function ActorCriticPolicy._build at 0x7fa20e156200>", "forward": "<function ActorCriticPolicy.forward at 0x7fa20e156290>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa20e156320>", "_predict": "<function ActorCriticPolicy._predict at 0x7fa20e1563b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa20e156440>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa20e1564d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa20e156560>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fa20e199c90>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651840188.722942, "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": 124, "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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+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 sha256:1fb4136818a85a42ad8a4a7acc9cc1d86c870d8485d5a6c62ef5c5161d42dcb5
3
+ size 144047
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 0x7fa20e130f80>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa20e156050>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa20e1560e0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa20e156170>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fa20e156200>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fa20e156290>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa20e156320>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fa20e1563b0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa20e156440>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa20e1564d0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa20e156560>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fa20e199c90>"
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": 507904,
46
+ "_total_timesteps": 500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1651840188.722942,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
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": 124,
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 sha256:54fc7d9036021688e0d315a19cf21c516b86b3b88b034339c4a0f8cfaea5134b
3
+ size 84829
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:85a09ef9b9cf7ef16f1f6bb2a5080e4ecac6dcd5cd6b1e0a07ff94a93401e85e
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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
2
+ Python: 3.7.13
3
+ Stable-Baselines3: 1.5.0
4
+ PyTorch: 1.11.0+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:11047bc7d0f8fa453b45257649ac4373936948cbc815d165ce1802997beb2b42
3
+ size 247361
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 215.57242515534307, "std_reward": 27.035471992209107, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-06T12:47:47.979852"}