crcdng commited on
Commit
c4ad819
1 Parent(s): 6d5c0fe

Initial commit

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ 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: 1859.70 +/- 599.36
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 sha256:588a5950c1063b8910a768ee0e279447839b64acd12b1695e7d1f243caf3539e
3
+ size 129243
a2c-AntBulletEnv-v0/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.8.0
a2c-AntBulletEnv-v0/data ADDED
@@ -0,0 +1,107 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7ea2ae023880>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ea2ae023910>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ea2ae0239a0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ea2ae023a30>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7ea2ae023ac0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7ea2ae023b50>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ea2ae023be0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ea2ae023c70>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7ea2ae023d00>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ea2ae023d90>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ea2ae023e20>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ea2ae023eb0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7ea2ca8faa80>"
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
+ "num_timesteps": 2000000,
36
+ "_total_timesteps": 2000000,
37
+ "_num_timesteps_at_start": 0,
38
+ "seed": null,
39
+ "action_noise": null,
40
+ "start_time": 1689711091508913852,
41
+ "learning_rate": 0.00096,
42
+ "tensorboard_log": null,
43
+ "lr_schedule": {
44
+ ":type:": "<class 'function'>",
45
+ ":serialized:": "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"
46
+ },
47
+ "_last_obs": {
48
+ ":type:": "<class 'numpy.ndarray'>",
49
+ ":serialized:": "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"
50
+ },
51
+ "_last_episode_starts": {
52
+ ":type:": "<class 'numpy.ndarray'>",
53
+ ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
54
+ },
55
+ "_last_original_obs": {
56
+ ":type:": "<class 'numpy.ndarray'>",
57
+ ":serialized:": "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"
58
+ },
59
+ "_episode_num": 0,
60
+ "use_sde": true,
61
+ "sde_sample_freq": -1,
62
+ "_current_progress_remaining": 0.0,
63
+ "_stats_window_size": 100,
64
+ "ep_info_buffer": {
65
+ ":type:": "<class 'collections.deque'>",
66
+ ":serialized:": "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"
67
+ },
68
+ "ep_success_buffer": {
69
+ ":type:": "<class 'collections.deque'>",
70
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
71
+ },
72
+ "_n_updates": 62500,
73
+ "n_steps": 8,
74
+ "gamma": 0.99,
75
+ "gae_lambda": 0.9,
76
+ "ent_coef": 0.0,
77
+ "vf_coef": 0.4,
78
+ "max_grad_norm": 0.5,
79
+ "normalize_advantage": false,
80
+ "observation_space": {
81
+ ":type:": "<class 'gym.spaces.box.Box'>",
82
+ ":serialized:": "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",
83
+ "dtype": "float32",
84
+ "_shape": [
85
+ 28
86
+ ],
87
+ "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]",
88
+ "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]",
89
+ "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]",
90
+ "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]",
91
+ "_np_random": null
92
+ },
93
+ "action_space": {
94
+ ":type:": "<class 'gym.spaces.box.Box'>",
95
+ ":serialized:": "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",
96
+ "dtype": "float32",
97
+ "_shape": [
98
+ 8
99
+ ],
100
+ "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]",
101
+ "high": "[1. 1. 1. 1. 1. 1. 1. 1.]",
102
+ "bounded_below": "[ True True True True True True True True]",
103
+ "bounded_above": "[ True True True True True True True True]",
104
+ "_np_random": null
105
+ },
106
+ "n_envs": 4
107
+ }
a2c-AntBulletEnv-v0/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:020516936cf4190ce587959a270cfbdfff8001c5dddc07c1a1c033c55f5b86bd
3
+ size 56190
a2c-AntBulletEnv-v0/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1fb9d5b85f3af37fd0230f15531aae70d58e045078adf6466db5c789a7e167bd
3
+ size 56894
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-5.15.109+-x86_64-with-glibc2.31 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 1.8.0
4
+ - PyTorch: 2.0.1+cu118
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 0x7ea2ae023880>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ea2ae023910>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ea2ae0239a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ea2ae023a30>", "_build": "<function ActorCriticPolicy._build at 0x7ea2ae023ac0>", "forward": "<function ActorCriticPolicy.forward at 0x7ea2ae023b50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ea2ae023be0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ea2ae023c70>", "_predict": "<function ActorCriticPolicy._predict at 0x7ea2ae023d00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ea2ae023d90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ea2ae023e20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ea2ae023eb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ea2ca8faa80>"}, "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}}, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1689711091508913852, "learning_rate": 0.00096, "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, "_stats_window_size": 100, "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, "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, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.31 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "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 sha256:26f9b488e62e799906112d19d327a428a46ec77cfadbf9ce81d8f8cb5346d916
3
+ size 1092364
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 1859.700991882477, "std_reward": 599.3550905488927, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-18T21:28:43.517269"}
vec_normalize.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:97b11590880bea38342743af6b2add2434f4eeea37b38c3dec4c082b1ea14e2d
3
+ size 2176