JonathanSum commited on
Commit
d459a45
1 Parent(s): a9d0c13

Add message

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
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7ff7530b8320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff7530b83b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff7530b8440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff7530b84d0>", "_build": "<function ActorCriticPolicy._build at 0x7ff7530b8560>", "forward": "<function ActorCriticPolicy.forward at 0x7ff7530b85f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff7530b8680>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff7530b8710>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff7530b87a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff7530b8830>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff7530b88c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff753081990>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1653310555.6492097, "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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 128, "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-model.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:054c3c0de1e249e97d1a0bda17d089bc7b2dd9777d7a4bc2657724112065a76a
3
+ size 144140
ppo-LunarLander-v2-model/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.0
ppo-LunarLander-v2-model/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
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 0x7ff7530b8320>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff7530b83b0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff7530b8440>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff7530b84d0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7ff7530b8560>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7ff7530b85f0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff7530b8680>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7ff7530b8710>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff7530b87a0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff7530b8830>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff7530b88c0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7ff753081990>"
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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1653310555.6492097,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "gASVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="
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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 128,
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-model/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ba17183163f309ab8cec70208002cfa2e41dd10e3d6739e208b2cf185341f282
3
+ size 84829
ppo-LunarLander-v2-model/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f80d87db8f9608d7d95c67891cb43c6033c78bef5b7b35a7b466d1e5279e4c3a
3
+ size 43201
ppo-LunarLander-v2-model/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-model/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
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 172.27211024605305, "std_reward": 98.598632398255, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-23T13:52:30.623437"}