Initial Commit for a PPO Lunarlander
Browse files- README.md +35 -1
- config.json +1 -0
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +95 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/system_info.txt +7 -0
- replay.mp4 +0 -0
- results.json +1 -0
README.md
CHANGED
@@ -1,3 +1,37 @@
|
|
1 |
---
|
2 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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: PPO
|
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: 260.58 +/- 25.83
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
---
|
23 |
+
|
24 |
+
# **PPO** Agent playing **LunarLander-v2**
|
25 |
+
This is a trained model of a **PPO** 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 0x7f77bcaeb280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f77bcaeb310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f77bcaeb3a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f77bcaeb430>", "_build": "<function ActorCriticPolicy._build at 0x7f77bcaeb4c0>", "forward": "<function ActorCriticPolicy.forward at 0x7f77bcaeb550>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f77bcaeb5e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f77bcaeb670>", "_predict": "<function ActorCriticPolicy._predict at 0x7f77bcaeb700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f77bcaeb790>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f77bcaeb820>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f77bcaeb8b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f77bcae7810>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677923500784920179, "learning_rate": 0.0003, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:80fc17e22701c8968cb45b1a1441f15c78c7313291e021dcd7cd32cd35fb2771
|
3 |
+
size 147344
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,95 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7f77bcaeb280>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f77bcaeb310>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f77bcaeb3a0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f77bcaeb430>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f77bcaeb4c0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f77bcaeb550>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f77bcaeb5e0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f77bcaeb670>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f77bcaeb700>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f77bcaeb790>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f77bcaeb820>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f77bcaeb8b0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7f77bcae7810>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"observation_space": {
|
25 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
26 |
+
":serialized:": "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",
|
27 |
+
"dtype": "float32",
|
28 |
+
"_shape": [
|
29 |
+
8
|
30 |
+
],
|
31 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
32 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
33 |
+
"bounded_below": "[False False False False False False False False]",
|
34 |
+
"bounded_above": "[False False False False False False False False]",
|
35 |
+
"_np_random": null
|
36 |
+
},
|
37 |
+
"action_space": {
|
38 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
39 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
40 |
+
"n": 4,
|
41 |
+
"_shape": [],
|
42 |
+
"dtype": "int64",
|
43 |
+
"_np_random": null
|
44 |
+
},
|
45 |
+
"n_envs": 16,
|
46 |
+
"num_timesteps": 1015808,
|
47 |
+
"_total_timesteps": 1000000,
|
48 |
+
"_num_timesteps_at_start": 0,
|
49 |
+
"seed": null,
|
50 |
+
"action_noise": null,
|
51 |
+
"start_time": 1677923500784920179,
|
52 |
+
"learning_rate": 0.0003,
|
53 |
+
"tensorboard_log": null,
|
54 |
+
"lr_schedule": {
|
55 |
+
":type:": "<class 'function'>",
|
56 |
+
":serialized:": "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"
|
57 |
+
},
|
58 |
+
"_last_obs": {
|
59 |
+
":type:": "<class 'numpy.ndarray'>",
|
60 |
+
":serialized:": "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"
|
61 |
+
},
|
62 |
+
"_last_episode_starts": {
|
63 |
+
":type:": "<class 'numpy.ndarray'>",
|
64 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
65 |
+
},
|
66 |
+
"_last_original_obs": null,
|
67 |
+
"_episode_num": 0,
|
68 |
+
"use_sde": false,
|
69 |
+
"sde_sample_freq": -1,
|
70 |
+
"_current_progress_remaining": -0.015808000000000044,
|
71 |
+
"ep_info_buffer": {
|
72 |
+
":type:": "<class 'collections.deque'>",
|
73 |
+
":serialized:": "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"
|
74 |
+
},
|
75 |
+
"ep_success_buffer": {
|
76 |
+
":type:": "<class 'collections.deque'>",
|
77 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
78 |
+
},
|
79 |
+
"_n_updates": 248,
|
80 |
+
"n_steps": 1024,
|
81 |
+
"gamma": 0.999,
|
82 |
+
"gae_lambda": 0.98,
|
83 |
+
"ent_coef": 0.01,
|
84 |
+
"vf_coef": 0.5,
|
85 |
+
"max_grad_norm": 0.5,
|
86 |
+
"batch_size": 64,
|
87 |
+
"n_epochs": 4,
|
88 |
+
"clip_range": {
|
89 |
+
":type:": "<class 'function'>",
|
90 |
+
":serialized:": "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"
|
91 |
+
},
|
92 |
+
"clip_range_vf": null,
|
93 |
+
"normalize_advantage": true,
|
94 |
+
"target_kl": null
|
95 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5583bb3df1b0474480a164d4f41b7d67e6ddf3a7f2b795381682c08438638a93
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a29d0e236f23eca79800c6b6b819646e7bbe89308e688e05384c8e81c7952559
|
3 |
+
size 43393
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
ppo-LunarLander-v2/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.8.10
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
+
- PyTorch: 1.13.1+cu116
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.22.4
|
7 |
+
- Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (239 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 260.5837960643443, "std_reward": 25.83407916632778, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-04T10:18:20.656199"}
|