Commit
·
2aefd64
1
Parent(s):
c79a4b1
first lunalander
Browse files- .gitattributes +1 -0
- README.md +28 -0
- config.json +1 -0
- ppo-LunarLander-v2-cufa.zip +3 -0
- ppo-LunarLander-v2-cufa/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2-cufa/data +94 -0
- ppo-LunarLander-v2-cufa/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2-cufa/policy.pth +3 -0
- ppo-LunarLander-v2-cufa/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2-cufa/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: 267.52 +/- 11.83
|
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 0x7f8eef982d40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8eef982dd0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8eef982e60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8eef982ef0>", "_build": "<function ActorCriticPolicy._build at 0x7f8eef982f80>", "forward": "<function ActorCriticPolicy.forward at 0x7f8eef98b050>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8eef98b0e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8eef98b170>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8eef98b200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8eef98b290>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8eef98b320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f8eef9d3990>"}, "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": 18, "num_timesteps": 1032192, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652216201.252016, "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:": "gAWVhQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYSAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLEoWUjAFDlHSUUpQu"}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.032192, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 280, "n_steps": 2048, "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": 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-5.4.188+-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-cufa.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1336bb9c73628736140dc69867df00b2109caff56b051661c82c8f90a8c00824
|
3 |
+
size 144182
|
ppo-LunarLander-v2-cufa/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.5.0
|
ppo-LunarLander-v2-cufa/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 0x7f8eef982d40>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8eef982dd0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8eef982e60>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8eef982ef0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f8eef982f80>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f8eef98b050>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8eef98b0e0>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f8eef98b170>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8eef98b200>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8eef98b290>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8eef98b320>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f8eef9d3990>"
|
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": 18,
|
45 |
+
"num_timesteps": 1032192,
|
46 |
+
"_total_timesteps": 1000000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1652216201.252016,
|
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:": "gAWVhQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYSAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLEoWUjAFDlHSUUpQu"
|
64 |
+
},
|
65 |
+
"_last_original_obs": null,
|
66 |
+
"_episode_num": 0,
|
67 |
+
"use_sde": false,
|
68 |
+
"sde_sample_freq": -1,
|
69 |
+
"_current_progress_remaining": -0.032192,
|
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": 280,
|
79 |
+
"n_steps": 2048,
|
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": 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-cufa/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:aeafb24136617029d4df62b9704e1c6c48fde4958e30155a58182966fc6a9522
|
3 |
+
size 84893
|
ppo-LunarLander-v2-cufa/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e8c226dc1f3c63d2c91395b16ee0d2ed198db9bbca905ced5066a312e7345c24
|
3 |
+
size 43201
|
ppo-LunarLander-v2-cufa/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-cufa/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:cae696c862e09dc7b50fd6c43ab46fa609e94f9cf52a45978b3019f91fbeb548
|
3 |
+
size 231185
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 267.5166042664397, "std_reward": 11.830603894440467, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-10T21:44:20.630751"}
|