brresnic commited on
Commit
54f5fb7
·
1 Parent(s): 2db828e

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: -150.86 +/- 74.20
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 0x7ffa05867290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ffa05867320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ffa058673b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ffa05867440>", "_build": "<function ActorCriticPolicy._build at 0x7ffa058674d0>", "forward": "<function ActorCriticPolicy.forward at 0x7ffa05867560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ffa058675f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ffa05867680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ffa05867710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ffa058677a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ffa05867830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ffa058a6cf0>"}, "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": 16384, "_total_timesteps": 10000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652574897.3089883, "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": -0.6384000000000001, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4, "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 sha256:2fbd71949b778e689114d700811fded4f6dac44d8b37b41028c35b0dfb7890b0
3
+ size 143910
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 0x7ffa05867290>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ffa05867320>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ffa058673b0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ffa05867440>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7ffa058674d0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7ffa05867560>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ffa058675f0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7ffa05867680>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ffa05867710>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ffa058677a0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ffa05867830>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7ffa058a6cf0>"
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": 16384,
46
+ "_total_timesteps": 10000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1652574897.3089883,
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": -0.6384000000000001,
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": 4,
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 sha256:10ce1d24276ce6accc84a953fca0424e7b4cbff77b63c37e7f2b6ab5b6aeb45f
3
+ size 84829
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5e468d515783f2686d9acccddaa12be9020d12d1c1ff301fa000871c2afa953e
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 sha256:43e16ab9bdabd74eec32e430cab9a2f9f1745a5606ddea54e48a788d21b1da6a
3
+ size 199653
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -150.85730399498715, "std_reward": 74.19708391387283, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-15T00:36:47.735425"}