Commit
•
ec170de
1
Parent(s):
765df71
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: 1493.01 +/- 157.73
|
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:ee5ed52279a578efc9f3514b5ac8c6bac668979ed328b68aa770a93ee7e48a45
|
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 0x7f3d92114310>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3d921143a0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3d92114430>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3d921144c0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f3d92114550>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f3d921145e0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3d92114670>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3d92114700>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f3d92114790>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3d92114820>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3d921148b0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3d92114940>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f3d920fba80>"
|
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": 1685355674372842550,
|
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 sha256:95929bd75dc9ec06b2edf763211f3bacc59efd6a08b7803ecc10b5b1adf17385
|
3 |
+
size 56190
|
a2c-AntBulletEnv-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5f9fed497d6af998a1ea0718f7cfa50689a62c8c05f31957e83027d34b68ad09
|
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 0x7f3d92114310>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3d921143a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3d92114430>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3d921144c0>", "_build": "<function ActorCriticPolicy._build at 0x7f3d92114550>", "forward": "<function ActorCriticPolicy.forward at 0x7f3d921145e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3d92114670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3d92114700>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3d92114790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3d92114820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3d921148b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3d92114940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f3d920fba80>"}, "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": 1685355674372842550, "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-5.15.107+-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 sha256:109408e975c5f1ade6bac7adaa41c12d65a4a8a3525f9cd2020e6b170e856acc
|
3 |
+
size 1161497
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 1493.0134100963828, "std_reward": 157.7347603605129, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-29T11:23:20.226707"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1f9244b718ba8f92c5f77ebdc4bb335f3ba6d564aeea7797867c17e5ee84e648
|
3 |
+
size 2176
|