initial_commit
Browse files- README.md +37 -0
- config.json +1 -0
- lunar_radar_v1.zip +3 -0
- lunar_radar_v1/_stable_baselines3_version +1 -0
- lunar_radar_v1/data +96 -0
- lunar_radar_v1/policy.optimizer.pth +3 -0
- lunar_radar_v1/policy.pth +3 -0
- lunar_radar_v1/pytorch_variables.pth +3 -0
- lunar_radar_v1/system_info.txt +9 -0
- replay.mp4 +0 -0
- results.json +1 -0
README.md
ADDED
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: stable-baselines3
|
3 |
+
tags:
|
4 |
+
- LunarLander-v2
|
5 |
+
- deep-reinforcement-learning
|
6 |
+
- reinforcement-learning
|
7 |
+
- stable-baselines3
|
8 |
+
model-index:
|
9 |
+
- name: lunar_radar
|
10 |
+
results:
|
11 |
+
- task:
|
12 |
+
type: reinforcement-learning
|
13 |
+
name: reinforcement-learning
|
14 |
+
dataset:
|
15 |
+
name: LunarLander-v2
|
16 |
+
type: LunarLander-v2
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: 280.01 +/- 17.33
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **lunar_radar** Agent playing **LunarLander-v2**
|
25 |
+
This is a trained model of a **lunar_radar** agent playing **LunarLander-v2**
|
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 |
+
```
|
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 0x7fb78da7a5f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb78da7a680>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb78da7a710>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb78da7a7a0>", "_build": "<function ActorCriticPolicy._build at 0x7fb78da7a830>", "forward": "<function ActorCriticPolicy.forward at 0x7fb78da7a8c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fb78da7a950>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb78da7a9e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb78da7aa70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb78da7ab00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb78da7ab90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb78da7ac20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fb78da803c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1686936650906937643, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": null, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "_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": 310, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "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": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
lunar_radar_v1.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:06cb948787ad2a6fac83e6675e220e8291b4a5847a47e408344382fab167da33
|
3 |
+
size 145903
|
lunar_radar_v1/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
lunar_radar_v1/data
ADDED
@@ -0,0 +1,96 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7fb78da7a5f0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb78da7a680>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb78da7a710>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb78da7a7a0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fb78da7a830>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fb78da7a8c0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fb78da7a950>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb78da7a9e0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fb78da7aa70>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb78da7ab00>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb78da7ab90>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb78da7ac20>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7fb78da803c0>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1015808,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1686936650906937643,
|
30 |
+
"learning_rate": 0.0003,
|
31 |
+
"tensorboard_log": null,
|
32 |
+
"_last_obs": null,
|
33 |
+
"_last_episode_starts": {
|
34 |
+
":type:": "<class 'numpy.ndarray'>",
|
35 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
36 |
+
},
|
37 |
+
"_last_original_obs": null,
|
38 |
+
"_episode_num": 0,
|
39 |
+
"use_sde": false,
|
40 |
+
"sde_sample_freq": -1,
|
41 |
+
"_current_progress_remaining": -0.015808000000000044,
|
42 |
+
"_stats_window_size": 100,
|
43 |
+
"ep_info_buffer": {
|
44 |
+
":type:": "<class 'collections.deque'>",
|
45 |
+
":serialized:": "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"
|
46 |
+
},
|
47 |
+
"ep_success_buffer": {
|
48 |
+
":type:": "<class 'collections.deque'>",
|
49 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
50 |
+
},
|
51 |
+
"_n_updates": 310,
|
52 |
+
"observation_space": {
|
53 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
54 |
+
":serialized:": "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",
|
55 |
+
"dtype": "float32",
|
56 |
+
"bounded_below": "[ True True True True True True True True]",
|
57 |
+
"bounded_above": "[ True True True True True True True True]",
|
58 |
+
"_shape": [
|
59 |
+
8
|
60 |
+
],
|
61 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
62 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
63 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
64 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
65 |
+
"_np_random": null
|
66 |
+
},
|
67 |
+
"action_space": {
|
68 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
69 |
+
":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
70 |
+
"n": "4",
|
71 |
+
"start": "0",
|
72 |
+
"_shape": [],
|
73 |
+
"dtype": "int64",
|
74 |
+
"_np_random": null
|
75 |
+
},
|
76 |
+
"n_envs": 16,
|
77 |
+
"n_steps": 2048,
|
78 |
+
"gamma": 0.99,
|
79 |
+
"gae_lambda": 0.95,
|
80 |
+
"ent_coef": 0.0,
|
81 |
+
"vf_coef": 0.5,
|
82 |
+
"max_grad_norm": 0.5,
|
83 |
+
"batch_size": 64,
|
84 |
+
"n_epochs": 10,
|
85 |
+
"clip_range": {
|
86 |
+
":type:": "<class 'function'>",
|
87 |
+
":serialized:": "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"
|
88 |
+
},
|
89 |
+
"clip_range_vf": null,
|
90 |
+
"normalize_advantage": true,
|
91 |
+
"target_kl": null,
|
92 |
+
"lr_schedule": {
|
93 |
+
":type:": "<class 'function'>",
|
94 |
+
":serialized:": "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"
|
95 |
+
}
|
96 |
+
}
|
lunar_radar_v1/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a948d0008bc85351436c0dd7fde69781a20610e6cdb9fd2e8e4ec3718f77a3c4
|
3 |
+
size 88057
|
lunar_radar_v1/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9f819213c23aa617430b72816dfc49161594680b223189e1a5b67bdf3adcad49
|
3 |
+
size 43329
|
lunar_radar_v1/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
lunar_radar_v1/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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: 2.0.0a5
|
4 |
+
- PyTorch: 2.0.1+cu118
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.22.4
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (172 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 280.0071956, "std_reward": 17.33425430283661, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-19T10:57:55.470327"}
|