ThetaPhiPsi
commited on
Commit
•
f22f4b3
1
Parent(s):
57795c9
Upload PPO LunarLander-v2 trained agent
Browse files- .gitattributes +1 -0
- README.md +28 -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 +3 -0
- results.json +1 -0
.gitattributes
CHANGED
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
25 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
26 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
27 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
25 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
26 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
27 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
28 |
+
*.mp4 filter=lfs diff=lfs merge=lfs -text
|
README.md
ADDED
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 |
+
- metrics:
|
12 |
+
- type: mean_reward
|
13 |
+
value: 250.75 +/- 19.39
|
14 |
+
name: mean_reward
|
15 |
+
task:
|
16 |
+
type: reinforcement-learning
|
17 |
+
name: reinforcement-learning
|
18 |
+
dataset:
|
19 |
+
name: LunarLander-v2
|
20 |
+
type: LunarLander-v2
|
21 |
+
---
|
22 |
+
|
23 |
+
# **PPO** Agent playing **LunarLander-v2**
|
24 |
+
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
|
25 |
+
|
26 |
+
## Usage (with Stable-baselines3)
|
27 |
+
TODO: Add your code
|
28 |
+
|
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 0x7f03287b97a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f03287b9830>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f03287b98c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f03287b9950>", "_build": "<function ActorCriticPolicy._build at 0x7f03287b99e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f03287b9a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f03287b9b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7f03287b9b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f03287b9c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f03287b9cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f03287b9d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f03287847e0>"}, "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": 1651782426.886289, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "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 sha256:8e071e31c8ace43060522b01c09ed4f20833e1ced317a2c1f4e9e1bb0d01f66a
|
3 |
+
size 144041
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.5.0
|
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 0x7f03287b97a0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f03287b9830>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f03287b98c0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f03287b9950>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f03287b99e0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f03287b9a70>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f03287b9b00>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f03287b9b90>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f03287b9c20>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f03287b9cb0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f03287b9d40>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f03287847e0>"
|
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": 1651782426.886289,
|
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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 248,
|
79 |
+
"n_steps": 1024,
|
80 |
+
"gamma": 0.999,
|
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": 4,
|
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 sha256:8c8ad3aaaeb03d294224580df9ea23d55e880807cec6789c43194b3f00014289
|
3 |
+
size 84829
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ed9fdda400f57253957a77d2c98fdff78bc5656ad3bae38285e1ad191d72cf49
|
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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
|
2 |
+
Python: 3.7.13
|
3 |
+
Stable-Baselines3: 1.5.0
|
4 |
+
PyTorch: 1.11.0+cu113
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:eccae09833c060410bacca8853bd33cf7952914722dd12d17cbf09f63f18fef7
|
3 |
+
size 254627
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 250.75450723919994, "std_reward": 19.390927403728096, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-05T20:52:27.898491"}
|