hmatzner commited on
Commit
36e70fa
·
1 Parent(s): 365584c

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: 1891.94 +/- 144.50
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 sha256:44bc6fe5e389cf5615d819c3ca25133645dccaa3a8bfd8a939bb1145a72c53db
3
+ size 129261
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 0x7f68048a3550>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f68048a35e0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f68048a3670>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f68048a3700>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f68048a3790>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f68048a3820>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f68048a38b0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f68048a3940>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f68048a39d0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f68048a3a60>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f68048a3af0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f68048a3b80>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f68048a4680>"
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": 2000000,
63
+ "_total_timesteps": 2000000,
64
+ "_num_timesteps_at_start": 0,
65
+ "seed": null,
66
+ "action_noise": null,
67
+ "start_time": 1678829333170555769,
68
+ "learning_rate": 0.00096,
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:": "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"
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": 62500,
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:ac477ef002efb341b831f7509ac3b828194482ae9041ee340ef0471ffb99c185
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:aa7db44a58410a722fc21c735162dbb5192714084b77550cb71f64bbdb94901b
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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.9.16
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
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 0x7f68048a3550>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f68048a35e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f68048a3670>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f68048a3700>", "_build": "<function ActorCriticPolicy._build at 0x7f68048a3790>", "forward": "<function ActorCriticPolicy.forward at 0x7f68048a3820>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f68048a38b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f68048a3940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f68048a39d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f68048a3a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f68048a3af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f68048a3b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f68048a4680>"}, "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": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1678829333170555769, "learning_rate": 0.00096, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAMxxWj/iuUe/L9y4PgELCr+3j0+/v+pXP5+RXT/mo1M+5rQ2P8YNDjusBQ5A44K2vA4nrL8gAps8X4ICwPK16T668E0/kTI2v/wa7b0H9Y2+9kPAvpkY+D2/o2a/93qHOzVeej9yOQo/ScEOP2E4l7/+bu8+KgDGPmouAD+WTfI/g9ktP6xB6j6DIAA/rDsdv6TLRL6yKiBAgUnuP7MxXD8euNI9oNnavwS+Sb4dQJG/0P6qPsUHoL/BnfI+ldiOP88yAz97ozU/QMqEv0vOfrw1Xno/cjkKP0nBDj9hOJe/PGj3vn4Ozr+M/gm/OR2Sv0HOMj2NiZM9zb1FPgooo76Y/zQ/2lvuO7BUkT42PAy8KHazP9G3rzp+c0A/j078u2mPAz9MosA7e7koP1ly8zvV97g/Ns4EPJG6yD6Ft2S8NV56P3I5Cj9JwQ4/ybBYP6KV4T4KXYm/bwcTPmRqJz8jynm/QupRP+PD4z2dnb0+MYM2PyfmTb1K8s6+hysZwBzU6b54V4M/dDFIv6hOUT8u/4A/ES/nP81TJz/w9yA9jl1Zv37efj4L0wk+57ROPx3hgr9yOQo/Q4rlv8mwWD+UjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLHIaUjAFDlHSUUpQu"}, "_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": 62500, "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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5149c9c69d86f0973fd64e22d4a27925c322f4a2b999dadf5203a92bcb83e087
3
+ size 1117018
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 1891.944794134653, "std_reward": 144.498574640677, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-14T22:36:48.660785"}
vec_normalize.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:34d692e82196b989c97b5e63cbc5f5effb7e2ab70695d5517cb92934ad5fcb8d
3
+ size 2136