sayby commited on
Commit
b857f13
1 Parent(s): 897f693

Unit 1 Tutorial

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 106.15 +/- 110.93
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
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 0x7fe00017f680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe00017f710>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe00017f7a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe00017f830>", "_build": "<function ActorCriticPolicy._build at 0x7fe00017f8c0>", "forward": "<function ActorCriticPolicy.forward at 0x7fe00017f950>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe00017f9e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe00017fa70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe00017fb00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe00017fb90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe00017fc20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe0001da0f0>"}, "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": 1668718786987042554, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "_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:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo_lunar_lander.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7b29cdc8caedcc440f334856bb8071fc6057f7ff7a09b9f70f16ef2192c3e274
3
+ size 147142
ppo_lunar_lander/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.2
ppo_lunar_lander/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 0x7fe00017f680>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe00017f710>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe00017f7a0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe00017f830>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fe00017f8c0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fe00017f950>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe00017f9e0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fe00017fa70>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe00017fb00>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe00017fb90>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe00017fc20>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fe0001da0f0>"
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": 1668718786987042554,
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:": "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"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo_lunar_lander/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:458329e1b886dab21e3c4390cea16427681d1a5393e9bc72d8f026f1fdbf8c32
3
+ size 87865
ppo_lunar_lander/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9fe7e6035d95f5c43707cde7462a0f16b4f12aef2184d1781e6507ec70438458
3
+ size 43201
ppo_lunar_lander/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_lunar_lander/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022
2
+ Python: 3.7.15
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.12.1+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (187 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 106.15162493514978, "std_reward": 110.92752051443564, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-11-17T21:13:11.254188"}