Commit
•
be6c79e
1
Parent(s):
fa24342
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 +94 -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: 266.12 +/- 19.15
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f9d38307ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9d38307d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9d38307dc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9d38307e50>", "_build": "<function ActorCriticPolicy._build at 0x7f9d38307ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f9d38307f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9d3830d040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9d3830d0d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9d3830d160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9d3830d1f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9d3830d280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f9d383854e0>"}, "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": 1671465744802567267, "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": 620, "n_steps": 1024, "gamma": 0.995, "gae_lambda": 0.98, "ent_coef": 0.01, "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, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "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:fbc7a64e0f3cbf423721ca39dd0706a3ec8f251e419c08783457186c55492137
|
3 |
+
size 147107
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.2
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,94 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f9d38307ca0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9d38307d30>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9d38307dc0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9d38307e50>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f9d38307ee0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f9d38307f70>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9d3830d040>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f9d3830d0d0>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9d3830d160>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9d3830d1f0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9d3830d280>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f9d383854e0>"
|
20 |
+
},
|
21 |
+
"verbose": 1,
|
22 |
+
"policy_kwargs": {},
|
23 |
+
"observation_space": {
|
24 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
25 |
+
":serialized:": "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",
|
26 |
+
"dtype": "float32",
|
27 |
+
"_shape": [
|
28 |
+
8
|
29 |
+
],
|
30 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
31 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
32 |
+
"bounded_below": "[False False False False False False False False]",
|
33 |
+
"bounded_above": "[False False False False False False False False]",
|
34 |
+
"_np_random": null
|
35 |
+
},
|
36 |
+
"action_space": {
|
37 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
38 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
39 |
+
"n": 4,
|
40 |
+
"_shape": [],
|
41 |
+
"dtype": "int64",
|
42 |
+
"_np_random": null
|
43 |
+
},
|
44 |
+
"n_envs": 16,
|
45 |
+
"num_timesteps": 1015808,
|
46 |
+
"_total_timesteps": 1000000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1671465744802567267,
|
51 |
+
"learning_rate": 0.0003,
|
52 |
+
"tensorboard_log": null,
|
53 |
+
"lr_schedule": {
|
54 |
+
":type:": "<class 'function'>",
|
55 |
+
":serialized:": "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"
|
56 |
+
},
|
57 |
+
"_last_obs": {
|
58 |
+
":type:": "<class 'numpy.ndarray'>",
|
59 |
+
":serialized:": "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"
|
60 |
+
},
|
61 |
+
"_last_episode_starts": {
|
62 |
+
":type:": "<class 'numpy.ndarray'>",
|
63 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
64 |
+
},
|
65 |
+
"_last_original_obs": null,
|
66 |
+
"_episode_num": 0,
|
67 |
+
"use_sde": false,
|
68 |
+
"sde_sample_freq": -1,
|
69 |
+
"_current_progress_remaining": -0.015808000000000044,
|
70 |
+
"ep_info_buffer": {
|
71 |
+
":type:": "<class 'collections.deque'>",
|
72 |
+
":serialized:": "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"
|
73 |
+
},
|
74 |
+
"ep_success_buffer": {
|
75 |
+
":type:": "<class 'collections.deque'>",
|
76 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
77 |
+
},
|
78 |
+
"_n_updates": 620,
|
79 |
+
"n_steps": 1024,
|
80 |
+
"gamma": 0.995,
|
81 |
+
"gae_lambda": 0.98,
|
82 |
+
"ent_coef": 0.01,
|
83 |
+
"vf_coef": 0.5,
|
84 |
+
"max_grad_norm": 0.5,
|
85 |
+
"batch_size": 64,
|
86 |
+
"n_epochs": 10,
|
87 |
+
"clip_range": {
|
88 |
+
":type:": "<class 'function'>",
|
89 |
+
":serialized:": "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"
|
90 |
+
},
|
91 |
+
"clip_range_vf": null,
|
92 |
+
"normalize_advantage": true,
|
93 |
+
"target_kl": null
|
94 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6458048927066f67925263e52a6fb61a7ecca3ee88803eb811ca46423001d2ac
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:803f74c4146baf43aa579408089af95f0ca70dbf0ff58b50dff95fb6da628bcd
|
3 |
+
size 43201
|
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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
|
2 |
+
Python: 3.8.16
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.13.0+cu116
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (207 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 266.1230185317175, "std_reward": 19.150618541932833, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-19T16:30:15.586610"}
|