mkahari commited on
Commit
255f150
·
1 Parent(s): fcef96b

Initial commit

Browse files
.gitattributes CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
32
  *.zip filter=lfs diff=lfs merge=lfs -text
33
  *.zst filter=lfs diff=lfs merge=lfs -text
34
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
32
  *.zip filter=lfs diff=lfs merge=lfs -text
33
  *.zst filter=lfs diff=lfs merge=lfs -text
34
  *tfevents* filter=lfs diff=lfs merge=lfs -text
35
+ replay.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - AntBulletEnv-v0
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: A2C
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: AntBulletEnv-v0
16
+ type: AntBulletEnv-v0
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 2388.90 +/- 100.02
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **A2C** Agent playing **AntBulletEnv-v0**
25
+ This is a trained model of a **A2C** agent playing **AntBulletEnv-v0**
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
+ ```
a2c-AntBulletEnv-v0.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:65ef6b5a62f1616f6f6b8b5b10507407683a373b1eecd03779011b6ae0865081
3
+ size 129259
a2c-AntBulletEnv-v0/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
a2c-AntBulletEnv-v0/data ADDED
@@ -0,0 +1,106 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f44865e7c10>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f44865e7ca0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f44865e7d30>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f44865e7dc0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f44865e7e50>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f44865e7ee0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f44865e7f70>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f44865eb040>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f44865eb0d0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f44865eb160>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f44865eb1f0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f44865eb280>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f44865d6c30>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {
24
+ ":type:": "<class 'dict'>",
25
+ ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
26
+ "log_std_init": -2,
27
+ "ortho_init": false,
28
+ "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
29
+ "optimizer_kwargs": {
30
+ "alpha": 0.99,
31
+ "eps": 1e-05,
32
+ "weight_decay": 0
33
+ }
34
+ },
35
+ "observation_space": {
36
+ ":type:": "<class 'gym.spaces.box.Box'>",
37
+ ":serialized:": "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",
38
+ "dtype": "float32",
39
+ "_shape": [
40
+ 28
41
+ ],
42
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
43
+ "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]",
44
+ "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
45
+ "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
46
+ "_np_random": null
47
+ },
48
+ "action_space": {
49
+ ":type:": "<class 'gym.spaces.box.Box'>",
50
+ ":serialized:": "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",
51
+ "dtype": "float32",
52
+ "_shape": [
53
+ 8
54
+ ],
55
+ "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]",
56
+ "high": "[1. 1. 1. 1. 1. 1. 1. 1.]",
57
+ "bounded_below": "[ True True True True True True True True]",
58
+ "bounded_above": "[ True True True True True True True True]",
59
+ "_np_random": null
60
+ },
61
+ "n_envs": 4,
62
+ "num_timesteps": 3000000,
63
+ "_total_timesteps": 3000000,
64
+ "_num_timesteps_at_start": 0,
65
+ "seed": null,
66
+ "action_noise": null,
67
+ "start_time": 1674145251436751874,
68
+ "learning_rate": 0.0005,
69
+ "tensorboard_log": null,
70
+ "lr_schedule": {
71
+ ":type:": "<class 'function'>",
72
+ ":serialized:": "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"
73
+ },
74
+ "_last_obs": {
75
+ ":type:": "<class 'numpy.ndarray'>",
76
+ ":serialized:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAB/PPj7eR4e9M7XJPpfk2j7x/QnAOzomv+i9cb4WoXc/o+Y1Pc47hr+J49++MPV5v/1g4r9Z/tq+qOBdv7+CAz9Zn1e+vacYwBSJUL9UvmU98UlXP6ucnr6oaZq+3rjPP7PCej+yM+Y+wP2Pv9Y2n7/SUzc/y4dsvw0WDL45qr0/ubykv7/cVD6pada+P4yGvtfUu77xE5a9F+dUv7xllz3PIMA+ryHSPnx2tjzocIY/xSCfPpImAUBsMXG/1LpyPw7TYb6L/O2/GzaTP+eJ9j6prIK/sjPmPseRYz+Qz00/4ohNP6XkNL+gA1Q9kKvtP1g+AcBQXl6/C24Cv6HEhr+Ac4e+aG/ZPaCS877oWBk+uiZTPzFATr7CgCU/ha6gP79akz9ngWK+mMCCvTU3Fj+BX6q/TVwjPbaq5j+m/A0/qayCv7Iz5j7A/Y+/kM9NP2ASWz/qkYy/KSiivpLAZT9HiArAmR5jvyoI5D1yX6K/CWkzPy1pDL/fnqG+r1duP2UnxD2QPPe/E4XxPuyLgr+k/nA/rgTCv27jn75h7FG/ld7FPrn1mz9HKKM/S7Pmv6msgr+yM+Y+x5FjP9Y2n7+UjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLHIaUjAFDlHSUUpQu"
77
+ },
78
+ "_last_episode_starts": {
79
+ ":type:": "<class 'numpy.ndarray'>",
80
+ ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
81
+ },
82
+ "_last_original_obs": {
83
+ ":type:": "<class 'numpy.ndarray'>",
84
+ ":serialized:": "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"
85
+ },
86
+ "_episode_num": 0,
87
+ "use_sde": true,
88
+ "sde_sample_freq": -1,
89
+ "_current_progress_remaining": 0.0,
90
+ "ep_info_buffer": {
91
+ ":type:": "<class 'collections.deque'>",
92
+ ":serialized:": "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"
93
+ },
94
+ "ep_success_buffer": {
95
+ ":type:": "<class 'collections.deque'>",
96
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
97
+ },
98
+ "_n_updates": 93750,
99
+ "n_steps": 8,
100
+ "gamma": 0.99,
101
+ "gae_lambda": 0.9,
102
+ "ent_coef": 0.0,
103
+ "vf_coef": 0.4,
104
+ "max_grad_norm": 0.5,
105
+ "normalize_advantage": false
106
+ }
a2c-AntBulletEnv-v0/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:61467ea0d29f85a40525944d86b3ed3b92085e4832ca7c250a36a5180ee08266
3
+ size 56190
a2c-AntBulletEnv-v0/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:45eff859855fb6d624a4750929bae242e408e6e65c05b53577beed79a43c9dd9
3
+ size 56958
a2c-AntBulletEnv-v0/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
a2c-AntBulletEnv-v0/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.10
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.21.6
7
+ - Gym: 0.21.0
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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f44865e7c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f44865e7ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f44865e7d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f44865e7dc0>", "_build": "<function ActorCriticPolicy._build at 0x7f44865e7e50>", "forward": "<function ActorCriticPolicy.forward at 0x7f44865e7ee0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f44865e7f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f44865eb040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f44865eb0d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f44865eb160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f44865eb1f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f44865eb280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f44865d6c30>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [28], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_np_random": null}, "n_envs": 4, "num_timesteps": 3000000, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1674145251436751874, "learning_rate": 0.0005, "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:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 93750, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:99e23cfd54f735623125d106b34b18881eba505c3a48d4570eeaedec75a3a587
3
+ size 1167043
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 2388.895638019836, "std_reward": 100.023941915304, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-19T17:37:22.919902"}
vec_normalize.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0bf36da5e48f5cf0c18e13de72752621504fa65be613f37022713ab4167fec1b
3
+ size 2521