Commit
•
39eeed7
1
Parent(s):
ffe16a9
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
@@ -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: 2081.25 +/- 50.17
|
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:ae2a10393285dc451635fa1a5be828805fc12ca2b1cb0018445de6b9594186a6
|
3 |
+
size 129246
|
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 0x7b5c9bc96710>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b5c9bc967a0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b5c9bc96830>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b5c9bc968c0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7b5c9bc96950>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7b5c9bc969e0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7b5c9bc96a70>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b5c9bc96b00>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7b5c9bc96b90>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b5c9bc96c20>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b5c9bc96cb0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7b5c9bc96d40>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7b5c9bc98080>"
|
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": 1689856138548382017,
|
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:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAKUs7z59jFA+OG64PjPPGT9X74o/+I8kwNw0jr/OWAW+NwMzPd7ujb+a0Be/xLk+QGD2+75NKFLAOQ0cP+1rn76bnTQ9XasBwEIdV78YTam/RrLDP1drIL2cFR4/sVBpvw4gQ7+Lcsi/YqadPp6wwr9709Y+wiUnP7uIB746ADM/WpbaPzosqj9DVrs+vuvZvqepEj8C78O/DmJDPx5/ib9t+C6+8GJpPw5MP79mimS+CvmUPwx/PL4mXMo+eYinPJ0Q3j5DHa6/1HV1P3lSqr0OIEO/ankjP2KmnT4ETyg/P6qvP4D+lT4se48+k7uxP1YOcj+A8ru+PFwhP4ZvOb9aOcq+/+YTvmzPhr+my7s9ysCfPxTzcL87HCO+Lma4PwfHAj9d1Ky/QUIzPqJODr9AaZS/iYlhPm0oGj4wiQY/DiBDv2p5Iz9ipp0+nrDCv7BWk78tHFo/KELnvlMcnb9UQby/SkgJO8OdRr4Nh8Q+orxlPnq3qL95bxS+JFErPTTPQ7+TojjAL/7BPoKHU7+g4k6+jOkFwFAizD6FzQc9YYXEP6EEZ74E8XS+wBG4PuXupz9qeSM/YqadPgRPKD+UjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwRLHIaUjAFDlHSUUpQu"
|
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:bb0b90325ba2ba77ec6cf136c379c5789cffa46a27558773da0b1c0c58ca36cd
|
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:e19ef8e90f4be17beecc38b60193d6926c644ddb061f7ddff85ec7ad7ba75bb3
|
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-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
|
2 |
+
- Python: 3.10.6
|
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 0x7b5c9bc96710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b5c9bc967a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b5c9bc96830>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b5c9bc968c0>", "_build": "<function ActorCriticPolicy._build at 0x7b5c9bc96950>", "forward": "<function ActorCriticPolicy.forward at 0x7b5c9bc969e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b5c9bc96a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b5c9bc96b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7b5c9bc96b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b5c9bc96c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b5c9bc96cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b5c9bc96d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b5c9bc98080>"}, "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": 1689856138548382017, "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:": "gAWVbQIAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLHIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWcAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/lGgLSxyFlIwBQ5R0lFKUjARoaWdolGgTKJZwAAAAAAAAAAAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH+UaAtLHIWUaBZ0lFKUjA1ib3VuZGVkX2JlbG93lGgTKJYcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLHIWUaBZ0lFKUjA1ib3VuZGVkX2Fib3ZllGgTKJYcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUaCJLHIWUaBZ0lFKUjApfbnBfcmFuZG9tlE51Yi4=", "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-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.6", "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 sha256:742177bba82600da97a674a62400857d6db0624212b7d8dc365fe474974f06d2
|
3 |
+
size 1258602
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 2081.252074552537, "std_reward": 50.17137053200093, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-20T13:24:29.611425"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:51e0b15decf7bfc1ae794f39e593a5178e7d90db1f7fc2552141971b9825284a
|
3 |
+
size 2176
|