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: 1518.19 +/- 180.36
|
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 sha256:96ebac22c17cd3c9c174e6e6c5dec676a0e5ea1cc1bb152a7acfa818e2a553b6
|
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 0x7fec79922680>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fec79922710>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fec799227a0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fec79922830>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fec799228c0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fec79922950>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fec799229e0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fec79922a70>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fec79922b00>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fec79922b90>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fec79922c20>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fec79922cb0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7fec799287c0>"
|
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": 1684890408577126390,
|
41 |
+
"learning_rate": 0.00096,
|
42 |
+
"tensorboard_log": null,
|
43 |
+
"lr_schedule": {
|
44 |
+
":type:": "<class 'function'>",
|
45 |
+
":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuCQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz9PdRBNVR1phZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
|
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 sha256:3734b9852838f5cc23a1b17d8c86f9790d2191828e3777ed4a45fdc68987c8d6
|
3 |
+
size 56190
|
a2c-AntBulletEnv-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:54c0d7bd220e5b13e8c96c1e482f0d6c972d194dcee1d07432a118d2eca71a92
|
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 0x7fec79922680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fec79922710>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fec799227a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fec79922830>", "_build": "<function ActorCriticPolicy._build at 0x7fec799228c0>", "forward": "<function ActorCriticPolicy.forward at 0x7fec79922950>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fec799229e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fec79922a70>", "_predict": "<function ActorCriticPolicy._predict at 0x7fec79922b00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fec79922b90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fec79922c20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fec79922cb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fec799287c0>"}, "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": 1684890408577126390, "learning_rate": 0.00096, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVNQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJbAAQAAAAAAAHDceT+6hVS/LFTdPoKv3T8+V4W/UiKjP5n+pL85h6q/kW1QPzxJ5D+oxxQ/pJMgvZentb+cXWU9KHr3PuCvGz+0dxa/Iat6vwDhgb4FC9Y/aPmEv1TMuT7tIgg/34J0PxgaXz/qfOo+l0a+PstXlr+3JOU9VkvtvzY8HL8T3Is/PFC3v5s/4b/nE5C/ee6SPhk3p75hA6C+qEA/v2AlL7wRqYS/8NuPP6H7Hz/ldFG/Crmcv4Tksz/P9hi/Aal5vTEg7r6ze9W8zWzmPv99EUDj35K/6nzqPpdGvj7LV5a/x8mOv0M15r/vaQS/YxKEPqEVaz877z0/acWXvvFjMj/hKGA/U6/mu14OQL+OXvK7DUd2v2B6mD+eYhw/F483v8rKlL+ESQhA3CdLPgufX7/Psoi/bbjgPrbhpr69XGe9GBpfP+p86j6XRr4+ffRZP10u2D63b8C/y2jcvd6grj8Czsm+HlAeP5SzNr+1NQq/uf1CP3HK8T+qQoY+P4RuPmAxuL8KIkg+u/CBPt+akz6/c7S+VD4Qv4b8Zb7g37c//vt1v68okD+O+L++YDGNPhgaXz/qfOo+l0a+PstXlr+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:": "gAWVpQEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAIC/AACAvwAAgL8AAIC/AACAvwAAgL8AAIC/AACAv5RoC0sIhZSMAUOUdJRSlIwEaGlnaJRoEyiWIAAAAAAAAAAAAIA/AACAPwAAgD8AAIA/AACAPwAAgD8AAIA/AACAP5RoC0sIhZRoFnSUUpSMDWJvdW5kZWRfYmVsb3eUaBMolggAAAAAAAAAAQEBAQEBAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBZ0lFKUjA1ib3VuZGVkX2Fib3ZllGgTKJYIAAAAAAAAAAEBAQEBAQEBlGgiSwiFlGgWdJRSlIwKX25wX3JhbmRvbZROdWIu", "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:d721ae4b23fb92b87cd247ed1dc4e6cc031d8607383e9204f132068bf4fd544b
|
3 |
+
size 1070615
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 1518.1868914881197, "std_reward": 180.3595591744856, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-24T02:11:50.291377"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:bcc06e683def164453c2a45ec6ab8fbc67efb00b7a166b8fd0cbe723a3610e09
|
3 |
+
size 2176
|