Initial 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: 2166.82 +/- 32.65
|
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 sha256:72d7ebe5d7eaaa27790f268083364ae46c14ec35b6238fa01650dda80ea87f3a
|
3 |
+
size 129248
|
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 0x7f2283105900>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2283105990>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2283105a20>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2283105ab0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f2283105b40>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f2283105bd0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f2283105c60>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2283105cf0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f2283105d80>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2283105e10>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2283105ea0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2283105f30>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f2283102bc0>"
|
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": 1685214974065323420,
|
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 sha256:703cf27f967ba8becffa17a51e16d1db5fd7d9db358d5cd6c472586e9b2d696f
|
3 |
+
size 56190
|
a2c-AntBulletEnv-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:53c8a3af770439bb94a1772fe2310d1f05ab96772ea768befeb6a3a39e18b1bc
|
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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
|
2 |
+
- Python: 3.10.11
|
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 0x7f2283105900>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2283105990>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2283105a20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2283105ab0>", "_build": "<function ActorCriticPolicy._build at 0x7f2283105b40>", "forward": "<function ActorCriticPolicy.forward at 0x7f2283105bd0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f2283105c60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2283105cf0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2283105d80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2283105e10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2283105ea0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2283105f30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f2283102bc0>"}, "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": 1685214974065323420, "learning_rate": 0.00096, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAJikMLz9/ig/tzQXvo5R2j8LFGQ/slZqv7v+TD5EdrC+7J4Lv48qKT+HlpI/nGnoP2FSrr9zmo2/eXEhvpaxW76xCba/jCFsP4+Bhz6FpGVAj1PGP/Xmh7+SnFY/lLPmP7/mmj9dYMG/3KyXPsfzyL9NHp8+f7KCP5tEMr/2Gow/ihlsP4k4Hb8L1d88fMgAPzKHGr/o6gu/gi80PxDP0T8mzKm/93U2wPZGAL/cBIU+wrBnvwPP67431U6/U778P3YV0j9yygK9Fv0svrFoVz+/5po/XWDBv9yslz7H88i/1mQVP0tbnD9LbpG/6qjePjZuaD8+LyDAg7igvsEtqj6oEGi+nunAP1IOlb7tarI/hqK9vhsh/r/Ewii+SgOfvvG4Qr8dcxVAR+WAv7yxxL/yf64/9YJDQNcfBr4IfwDAhIpTv11gwb/crJc+x/PIvwL7Lz/EaYs/C5FUv1e9hD8KmwJAbOy1P+LXQj9APg2/gVs+PbTlk7+FqAE/met7v/TaRz/v1E4/PsEnvwUEcT5y20U/UdZUv0xiAz8ckZk8PpxuPt7gx78ihk0/1fo3voSKU7+ucyk/3KyXPkgQIz+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, "_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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "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:b9b82537d9ed7b839a67f7d533cea4f3f45c197dfc6e2768979d78c16dd0dcae
|
3 |
+
size 1255631
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 2166.824695474375, "std_reward": 32.64764261001412, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-27T20:43:53.062246"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:79f6cbb3cb073c0a432e1623d45f59eea62a342d1c1934dfb5006c79e3fe937b
|
3 |
+
size 2176
|