Initial commit
Browse files- 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
- results.json +1 -0
- vec_normalize.pkl +3 -0
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: 1342.37 +/- 105.46
|
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 sha256:8f97013e31cb6acc22b84927a51d55e9b3b2926fc3c3988f4b91a94cdac0911c
|
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 0x7f8d0c9f8040>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8d0c9f80d0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8d0c9f8160>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8d0c9f81f0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f8d0c9f8280>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f8d0c9f8310>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8d0c9f83a0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8d0c9f8430>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f8d0c9f84c0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8d0c9f8550>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8d0c9f85e0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8d0c9f8670>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f8d0c9eef40>"
|
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": 1000000,
|
36 |
+
"_total_timesteps": 1000000,
|
37 |
+
"_num_timesteps_at_start": 0,
|
38 |
+
"seed": null,
|
39 |
+
"action_noise": null,
|
40 |
+
"start_time": 1687026254880108860,
|
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": 31943,
|
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 sha256:5e0d3b144ebd342953c1b22aa88c04bf3ec21edc5f8ca5aec975215ececf4c01
|
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:a2dd39d709212e7869154d86b3de9d952712fba7e55dade2b62170358f65fe43
|
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: 3.10.12
|
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 0x7f8d0c9f8040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8d0c9f80d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8d0c9f8160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8d0c9f81f0>", "_build": "<function ActorCriticPolicy._build at 0x7f8d0c9f8280>", "forward": "<function ActorCriticPolicy.forward at 0x7f8d0c9f8310>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8d0c9f83a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8d0c9f8430>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8d0c9f84c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8d0c9f8550>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8d0c9f85e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8d0c9f8670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f8d0c9eef40>"}, "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": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1687026254880108860, "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": 31943, "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": "3.10.12", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 1342.3655911386745, "std_reward": 105.46393829326882, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-17T19:10:33.799102"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:efb4be7deded975e3116968c5a679c87b80694b3715bb59dd3642b5d1474f070
|
3 |
+
size 2176
|