micheljperez commited on
Commit
4451815
1 Parent(s): c7c9b36

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: 248.29 +/- 40.02
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 0x7fefab887f80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fefab88d050>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fefab88d0e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fefab88d170>", "_build": "<function ActorCriticPolicy._build at 0x7fefab88d200>", "forward": "<function ActorCriticPolicy.forward at 0x7fefab88d290>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fefab88d320>", "_predict": "<function ActorCriticPolicy._predict at 0x7fefab88d3b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fefab88d440>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fefab88d4d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fefab88d560>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fefab8c8e10>"}, "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, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652042383.4863095, "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": 310, "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-5.4.188+-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 sha256:9ab6468e651dbf7725126a7887b449b64f113af5a1eddc6c69f4245ddaabb744
3
+ size 144017
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 0x7fefab887f80>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fefab88d050>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fefab88d0e0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fefab88d170>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fefab88d200>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fefab88d290>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fefab88d320>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fefab88d3b0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fefab88d440>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fefab88d4d0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fefab88d560>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fefab8c8e10>"
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": 1652042383.4863095,
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": 310,
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:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
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:c1669d42bd9772ed28d345a6745cc231820a0bf46648e5a0a619b46993a2e7ca
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:d23d85bc46bede8bcc2d3bc090fb3036c8bde4f7905021e88816fb22fa321429
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:d2fb7a9b47bc5e434b043e43bd9312f706ff72da2f8496ab07dabf821f8983cb
3
+ size 202482
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 248.28976016684274, "std_reward": 40.01876024672722, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-08T21:18:27.708178"}