efawe commited on
Commit
0f6f772
1 Parent(s): 655331d

First test upload of lunarLander

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: 194.27 +/- 27.14
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 0x7f9c3cf20dd0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9c3cf20e60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9c3cf20ef0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9c3cf20f80>", "_build": "<function ActorCriticPolicy._build at 0x7f9c3cf28050>", "forward": "<function ActorCriticPolicy.forward at 0x7f9c3cf280e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9c3cf28170>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9c3cf28200>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9c3cf28290>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9c3cf28320>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9c3cf283b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f9c3cf71540>"}, "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:": "gAWVgQAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZRoB5OUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=", "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": 1651953174.4672978, "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": "0.17.3"}}
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:354c266667729557180dbd4543fd63a817c87ee4c4038c2a6a1085944dd031f3
3
+ size 264289
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 194.2689015468829, "std_reward": 27.144097967949882, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-07T20:02:54.300889"}
test.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:13e556306d9eb3b4cf1c7997b86264dcb1b47e37244491b346d4749c32664623
3
+ size 144046
test/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.0
test/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 0x7f9c3cf20dd0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9c3cf20e60>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9c3cf20ef0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9c3cf20f80>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f9c3cf28050>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f9c3cf280e0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9c3cf28170>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f9c3cf28200>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9c3cf28290>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9c3cf28320>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9c3cf283b0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f9c3cf71540>"
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:": "gAWVgQAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZRoB5OUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=",
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": 1651953174.4672978,
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": 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:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
test/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9ee6d242a60dad1d0df77ae16f1092e8d1c26a461a2d6f1cc9ccb636fc150d4a
3
+ size 84829
test/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f196f36a47374a7701905bb4831ab1b07a3205c887035b0dfd8649983d45de09
3
+ size 43201
test/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
test/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: 0.17.3