Commit
·
cce8677
1
Parent(s):
018a7a0
Upload PPO LunarLander-v2 trained agent
Browse files- README.md +37 -0
- 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
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: 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: 246.68 +/- 20.03
|
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 0x7ffb13472af0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ffb13472b80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ffb13472c10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ffb13472ca0>", "_build": "<function ActorCriticPolicy._build at 0x7ffb13472d30>", "forward": "<function ActorCriticPolicy.forward at 0x7ffb13472dc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ffb13472e50>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ffb13472ee0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ffb13472f70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ffb13477040>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ffb134770d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ffb13477160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ffb1346be70>"}, "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": 1678237302118805805, "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 sha256:48f57140145a218b15ea6844a57650f310c7188cb848dc68b068aeb0b42dfa3f
|
3 |
+
size 147416
|
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 0x7ffb13472af0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ffb13472b80>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ffb13472c10>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ffb13472ca0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7ffb13472d30>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7ffb13472dc0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7ffb13472e50>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ffb13472ee0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7ffb13472f70>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ffb13477040>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ffb134770d0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7ffb13477160>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7ffb1346be70>"
|
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": 1678237302118805805,
|
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:f4acd994f03d1c860e6cf4227b75256dd0a14c37eb20302a68c7d9b362649fef
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:71276cb311adb3633e0d858ae28ab77eb9b24624af9a4452af162fc0e952344f
|
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 (196 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 246.68047036288453, "std_reward": 20.034278362802933, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-08T01:51:14.837202"}
|