First commit
Browse files- .gitattributes +1 -0
- README.md +37 -0
- a2c-AntBulletEnv-v0.zip +3 -0
- a2c-AntBulletEnv-v0/_stable_baselines3_version +1 -0
- a2c-AntBulletEnv-v0/data +107 -0
- a2c-AntBulletEnv-v0/policy.optimizer.pth +3 -0
- a2c-AntBulletEnv-v0/policy.pth +3 -0
- a2c-AntBulletEnv-v0/pytorch_variables.pth +3 -0
- a2c-AntBulletEnv-v0/system_info.txt +7 -0
- config.json +1 -0
- replay.mp4 +3 -0
- results.json +1 -0
- vec_normalize.pkl +3 -0
.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: 2103.44 +/- 51.90
|
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 sha256:6655b5977de8101a25978c2bce7a0e475bd102038f7afe338a18918781e2ea3a
|
3 |
+
size 129231
|
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 0x7f153e279280>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f153e279310>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f153e2793a0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f153e279430>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f153e2794c0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f153e279550>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f153e2795e0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f153e279670>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f153e279700>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f153e279790>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f153e279820>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f153e2798b0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f153e27a840>"
|
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": 2500000,
|
36 |
+
"_total_timesteps": 2500000,
|
37 |
+
"_num_timesteps_at_start": 0,
|
38 |
+
"seed": null,
|
39 |
+
"action_noise": null,
|
40 |
+
"start_time": 1681746046674796412,
|
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:": "gAWVRAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQJxxdCzC1qqMAWyUTegDjAF0lEdAwQA/GhmGunV9lChoBkdAm7SER3/xUmgHTegDaAhHQMEA6peeFtd1fZQoaAZHQJwdYXGff41oB03oA2gIR0DBAgK88La3dX2UKGgGR0CfNssjFAE/aAdN6ANoCEdAwQJ/RZU1h3V9lChoBkdAnb8FJg9eQmgHTegDaAhHQMED77212JV1fZQoaAZHQJ8djF6zE75oB03oA2gIR0DBBRdvCMxXdX2UKGgGR0CYRcb7j1f3aAdN6ANoCEdAwQY+TTOPenV9lChoBkdAm+nNy5qdpmgHTegDaAhHQMEGp7UXpGF1fZQoaAZHQJfqaohpxm1oB03oA2gIR0DBB435JsfrdX2UKGgGR0CeJnaMaS9vaAdN6ANoCEdAwQg4zPa+OHV9lChoBkdAnRP4vrWy1WgHTegDaAhHQMEJWpgb6xh1fZQoaAZHQJ5bsfgaWHFoB03oA2gIR0DBCcQkka/AdX2UKGgGR0CdoIyTINmUaAdN6ANoCEdAwQr7+GXXy3V9lChoBkdAn2TiNjslcGgHTegDaAhHQMEMGUNBnjB1fZQoaAZHQJPmLW8RL9NoB03oA2gIR0DBDYvfdhy9dX2UKGgGR0CXliafzz3AaAdN6ANoCEdAwQ35ZVXFLnV9lChoBkdAnHffT1CgLGgHTegDaAhHQMEO/yAQQMB1fZQoaAZHQJw4GblRxcVoB03oA2gIR0DBD7Zi7TUidX2UKGgGR0CYyMFV1fVqaAdN6ANoCEdAwRDZAt4A0nV9lChoBkdAmIMFkhA4XGgHTegDaAhHQMERQpj2Bat1fZQoaAZHQJPRg4n4O+ZoB03oA2gIR0DBElunO0LMdX2UKGgGR0CS7uSxZ+x4aAdN6ANoCEdAwRNogh8pkXV9lChoBkdAeiU+C9RJmWgHTegDaAhHQMEU9W38XN11fZQoaAZHQJog6ksSTQpoB03oA2gIR0DBFVvGlyimdX2UKGgGR0B8xki9qUNbaAdN6ANoCEdAwRZO7ZnL73V9lChoBkdAlJEbdJrckGgHTegDaAhHQMEXAWOhkAh1fZQoaAZHQI0i17pmmLtoB03oA2gIR0DBGCNHWjGldX2UKGgGR0CXKE4rSVnmaAdN6ANoCEdAwRiIZhrnDHV9lChoBkdAmNhlNUOuq2gHTegDaAhHQMEZcFfzBhx1fZQoaAZHQJub6+oLofVoB03oA2gIR0DBGnAd4mkWdX2UKGgGR0CcEBg9Net0aAdN6ANoCEdAwRxCKqn3tnV9lChoBkdAngWrqQiiZmgHTegDaAhHQMEcpM1KoQ51fZQoaAZHQJ4WSP7vXshoB03oA2gIR0DBHZc2m52AdX2UKGgGR0CbKvMBZIQOaAdN6ANoCEdAwR5KdyT6i3V9lChoBkdAn45/MSsbN2gHTegDaAhHQMEfdqp97Wx1fZQoaAZHQJzPDNwBHTZoB03oA2gIR0DBH+KaXrt3dX2UKGgGR0CezvaAnUlSaAdN6ANoCEdAwSDOkyk9EHV9lChoBkdAn0Wf2PDHfmgHTegDaAhHQMEhme/xlQN1fZQoaAZHQJ/84/dIoVpoB03oA2gIR0DBI118qnWKdX2UKGgGR0CgICO+AVfvaAdN6ANoCEdAwSQCLv1DjXV9lChoBkdAoEaToQnQY2gHTegDaAhHQMEk6f4h2W91fZQoaAZHQJ5/tMyrPt5oB03oA2gIR0DBJZca4tpVdX2UKGgGR0CcmcYs/Y8MaAdN6ANoCEdAwSa6zC1qnHV9lChoBkdAnnh9WIXTE2gHTegDaAhHQMEnJNY8uBd1fZQoaAZHQJ76Ez0pVjtoB03oA2gIR0DBKBZG4I8hdX2UKGgGR0Cfu0QVKwpwaAdN6ANoCEdAwSjPO4XoDHV9lChoBkdAn3xnoPkJbGgHTegDaAhHQMEqe2ZqmCR1fZQoaAZHQKAQ8lQdjoZoB03oA2gIR0DBKynGn4widX2UKGgGR0CgZ8TFl05maAdN6ANoCEdAwSxXDgIhQnV9lChoBkdAkWeQL7XQMWgHTegDaAhHQMEtCxTKkmB1fZQoaAZHQKAnEwKSgXdoB03oA2gIR0DBLii7VawEdX2UKGgGR0CeOJjABT4taAdN6ANoCEdAwS6VJbMX8HV9lChoBkdAnHkJrxiG4GgHTegDaAhHQMEvgq8L8aZ1fZQoaAZHQJ8WCeoUBXFoB03oA2gIR0DBMDXhhpg1dX2UKGgGR0CeBMWldkauaAdN6ANoCEdAwTGzYwIt2HV9lChoBkdAnH4jJlrdnGgHTegDaAhHQMEyWUmdAgR1fZQoaAZHQKAwfoUSIxhoB03oA2gIR0DBM7FZJTVEdX2UKGgGR0CcwTHWjGkvaAdN6ANoCEdAwTRgkKNQ03V9lChoBkdAnuKLx/d69mgHTegDaAhHQME1fng5zYF1fZQoaAZHQJ1523Ytg8doB03oA2gIR0DBNeefXf65dX2UKGgGR0Cc8iazu4PPaAdN6ANoCEdAwTbYEzwc53V9lChoBkdAnWZ7l3hXKmgHTegDaAhHQME3jmEf1Yh1fZQoaAZHQJ8ZePq9oOBoB03oA2gIR0DBOOAT7EYPdX2UKGgGR0CgN29lVcUuaAdN6ANoCEdAwTmDfsu3+nV9lChoBkdAoAcP7DVH4GgHTegDaAhHQME7DVivxH51fZQoaAZHQJ5wZcJMQEpoB03oA2gIR0DBO+MmhM8HdX2UKGgGR0CcKTyc0+C9aAdN6ANoCEdAwT0Ius90R3V9lChoBkdAn+qo+nqFAWgHTegDaAhHQME9eJDeCTV1fZQoaAZHQKAV6YNy5qdoB03oA2gIR0DBPl4JokAxdX2UKGgGR0ChBiqwY+B6aAdN6ANoCEdAwT8GxrzoU3V9lChoBkdAoBagfp2U0WgHTegDaAhHQMFAIWU0Nz91fZQoaAZHQJ/eVUWEbo9oB03oA2gIR0DBQKbU5MlDdX2UKGgGR0CgSn+717IDaAdN6ANoCEdAwUIgOJcgQ3V9lChoBkdAngQzTz/ZNGgHTegDaAhHQMFDOFpGnXN1fZQoaAZHQKA207PIGQloB03oA2gIR0DBREzoW56MdX2UKGgGR0CfylzPrv9caAdN6ANoCEdAwUSv8EV32XV9lChoBkdAoEsgsd1dPmgHTegDaAhHQMFFlE7fYSR1fZQoaAZHQJ6mQiKR+0BoB03oA2gIR0DBRkCMir1edX2UKGgGR0CfH9yTY/VzaAdN6ANoCEdAwUdZu5SWJXV9lChoBkdAn6fuyVv/BGgHTegDaAhHQMFHwtRekYZ1fZQoaAZHQKAF8Er5IpZoB03oA2gIR0DBSPV8XvYwdX2UKGgGR0CgerUdRzikaAdN6ANoCEdAwUof4iX6ZnV9lChoBkdAoHJSrq+rVGgHTegDaAhHQMFLqcMEzO51fZQoaAZHQKDMbfTkQwtoB03oA2gIR0DBTBAfyPMjdX2UKGgGR0Cgg270OEuhaAdN6ANoCEdAwUz4Nz8xbnV9lChoBkdAn546Ii1RcmgHTegDaAhHQMFNpGQSzxB1fZQoaAZHQKAOob5M10loB03oA2gIR0DBTr210DEFdX2UKGgGR0CfBDDhtLteaAdN6ANoCEdAwU8ihKUVz3V9lChoBkdAoAruvllsg2gHTegDaAhHQMFQCuSntOV1fZQoaAZHQJ6NPjWCmMxoB03oA2gIR0DBUQ2WrwOOdX2UKGgGR0Cf45+Y+jdpaAdN6ANoCEdAwVLpPIn0CnV9lChoBkdAoJNDLW7OFGgHTegDaAhHQMFTVJv5xip1fZQoaAZHQJ/ETfbblBBoB03oA2gIR0DBVEwBJZntdX2UKGgGR0CgPoda+vhZaAdN6ANoCEdAwVT4JHiFTXV9lChoBkdAn5UJ1RtP6GgHTegDaAhHQMFWDsb3oLZ1fZQoaAZHQKDTTsAvL5hoB03oA2gIR0DBVnM/jbSJdX2UKGgGR0CfE6LR8c+8aAdN6ANoCEdAwVdcuFHrhXV9lChoBkdAnN2+DrZ8KGgHTegDaAhHQMFYIt34bjt1fZQoaAZHQKE+AOpbUw1oB03oA2gIR0DBWfGtwJgLdX2UKGgGR0CdTL4RVZLaaAdN6ANoCEdAwVqp/dZaFHVlLg=="
|
67 |
+
},
|
68 |
+
"ep_success_buffer": {
|
69 |
+
":type:": "<class 'collections.deque'>",
|
70 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
71 |
+
},
|
72 |
+
"_n_updates": 78125,
|
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 sha256:946d3999bffbdd5c49283be21ccf31cc7daa1ceb1d4afdb30bed15e38856b100
|
3 |
+
size 56190
|
a2c-AntBulletEnv-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9f4de1eb311d6489a31bc8eb5c718d1c5e815304d445a55b52afc863822d40cd
|
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-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.9.16
|
3 |
+
- Stable-Baselines3: 1.8.0
|
4 |
+
- PyTorch: 2.0.0+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 0x7f153e279280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f153e279310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f153e2793a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f153e279430>", "_build": "<function ActorCriticPolicy._build at 0x7f153e2794c0>", "forward": "<function ActorCriticPolicy.forward at 0x7f153e279550>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f153e2795e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f153e279670>", "_predict": "<function ActorCriticPolicy._predict at 0x7f153e279700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f153e279790>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f153e279820>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f153e2798b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f153e27a840>"}, "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": 2500000, "_total_timesteps": 2500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681746046674796412, "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": 78125, "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-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+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 sha256:4b17bb159fe41bf2e9df62d0692b5996ef69b77cda520418cc0f0c2005aa1a7c
|
3 |
+
size 1047353
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 2103.439646316366, "std_reward": 51.89575521012552, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-17T17:09:54.309158"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:7a5515a90a8148b144754e97857840711c5fbe8e9f879d3c27f5e318b8f67c2e
|
3 |
+
size 2170
|