marleyshan21
commited on
Commit
•
292be4a
1
Parent(s):
38ac1c2
Tried 4th time 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 +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 +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: 281.35 +/- 15.31
|
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 0x7f78f4d49a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f78f4d49ae8>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f78f4d49b70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f78f4d49bf8>", "_build": "<function ActorCriticPolicy._build at 0x7f78f4d49c80>", "forward": "<function ActorCriticPolicy.forward at 0x7f78f4d49d08>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f78f4d49d90>", "_predict": "<function ActorCriticPolicy._predict at 0x7f78f4d49e18>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f78f4d49ea0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f78f4d49f28>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f78f4d4c048>", "__abstractmethods__": "frozenset()", "_abc_registry": "<_weakrefset.WeakSet object at 0x7f78f4d3db38>", "_abc_cache": "<_weakrefset.WeakSet object at 0x7f78f4d3db70>", "_abc_negative_cache": "<_weakrefset.WeakSet object at 0x7f78f4d3dba8>", "_abc_negative_cache_version": 58}, "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:": "gAWVhwAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZSMBWR0eXBllJOUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=", "n": 4, "shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 9011200, "_total_timesteps": 9000000, "seed": null, "action_noise": null, "start_time": 1651853376.920396, "learning_rate": 0.0001, "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": -0.0012444444444443814, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1100, "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": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "target_kl": null, "system_info": {"OS": "Linux-5.4.0-70-generic-x86_64-with-debian-buster-sid #78~18.04.1-Ubuntu SMP Sat Mar 20 14:10:07 UTC 2021", "Python": "3.6.15", "Stable-Baselines3": "1.3.0", "PyTorch": "1.10.2+cu102", "GPU Enabled": "True", "Numpy": "1.19.5", "Gym": "0.19.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c3bbfefc4de8a06ec405872b3f1a934c918a9ff3ee7eb7b357f8cd22d618e2c6
|
3 |
+
size 144274
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.3.0
|
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 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 0x7f78f4d49a60>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f78f4d49ae8>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f78f4d49b70>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f78f4d49bf8>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f78f4d49c80>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f78f4d49d08>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f78f4d49d90>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f78f4d49e18>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f78f4d49ea0>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f78f4d49f28>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f78f4d4c048>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_registry": "<_weakrefset.WeakSet object at 0x7f78f4d3db38>",
|
20 |
+
"_abc_cache": "<_weakrefset.WeakSet object at 0x7f78f4d3db70>",
|
21 |
+
"_abc_negative_cache": "<_weakrefset.WeakSet object at 0x7f78f4d3dba8>",
|
22 |
+
"_abc_negative_cache_version": 58
|
23 |
+
},
|
24 |
+
"verbose": 1,
|
25 |
+
"policy_kwargs": {},
|
26 |
+
"observation_space": {
|
27 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
28 |
+
":serialized:": "gAWVpAEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBXNoYXBllEsIhZSMA2xvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/lGgLSwiFlIwBQ5R0lFKUjARoaWdolGgTKJYgAAAAAAAAAAAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/lGgLSwiFlGgWdJRSlIwNYm91bmRlZF9iZWxvd5RoEyiWCAAAAAAAAAAAAAAAAAAAAJRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZRoFnSUUpSMDWJvdW5kZWRfYWJvdmWUaBMolggAAAAAAAAAAAAAAAAAAACUaCJLCIWUaBZ0lFKUjApfbnBfcmFuZG9tlE51Yi4=",
|
29 |
+
"dtype": "float32",
|
30 |
+
"shape": [
|
31 |
+
8
|
32 |
+
],
|
33 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
34 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
35 |
+
"bounded_below": "[False False False False False False False False]",
|
36 |
+
"bounded_above": "[False False False False False False False False]",
|
37 |
+
"_np_random": null
|
38 |
+
},
|
39 |
+
"action_space": {
|
40 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
41 |
+
":serialized:": "gAWVhwAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZSMBWR0eXBllJOUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=",
|
42 |
+
"n": 4,
|
43 |
+
"shape": [],
|
44 |
+
"dtype": "int64",
|
45 |
+
"_np_random": null
|
46 |
+
},
|
47 |
+
"n_envs": 16,
|
48 |
+
"num_timesteps": 9011200,
|
49 |
+
"_total_timesteps": 9000000,
|
50 |
+
"seed": null,
|
51 |
+
"action_noise": null,
|
52 |
+
"start_time": 1651853376.920396,
|
53 |
+
"learning_rate": 0.0001,
|
54 |
+
"tensorboard_log": null,
|
55 |
+
"lr_schedule": {
|
56 |
+
":type:": "<class 'function'>",
|
57 |
+
":serialized:": "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"
|
58 |
+
},
|
59 |
+
"_last_obs": {
|
60 |
+
":type:": "<class 'numpy.ndarray'>",
|
61 |
+
":serialized:": "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"
|
62 |
+
},
|
63 |
+
"_last_episode_starts": {
|
64 |
+
":type:": "<class 'numpy.ndarray'>",
|
65 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
66 |
+
},
|
67 |
+
"_last_original_obs": null,
|
68 |
+
"_episode_num": 0,
|
69 |
+
"use_sde": false,
|
70 |
+
"sde_sample_freq": -1,
|
71 |
+
"_current_progress_remaining": -0.0012444444444443814,
|
72 |
+
"ep_info_buffer": {
|
73 |
+
":type:": "<class 'collections.deque'>",
|
74 |
+
":serialized:": "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"
|
75 |
+
},
|
76 |
+
"ep_success_buffer": {
|
77 |
+
":type:": "<class 'collections.deque'>",
|
78 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
79 |
+
},
|
80 |
+
"_n_updates": 1100,
|
81 |
+
"n_steps": 2048,
|
82 |
+
"gamma": 0.999,
|
83 |
+
"gae_lambda": 0.98,
|
84 |
+
"ent_coef": 0.01,
|
85 |
+
"vf_coef": 0.5,
|
86 |
+
"max_grad_norm": 0.5,
|
87 |
+
"batch_size": 64,
|
88 |
+
"n_epochs": 4,
|
89 |
+
"clip_range": {
|
90 |
+
":type:": "<class 'function'>",
|
91 |
+
":serialized:": "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"
|
92 |
+
},
|
93 |
+
"clip_range_vf": null,
|
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:b0f4f5f0617d420ad4842c3bcb08cd36ac1c9dbb6a10909617cfb6f1f27368fd
|
3 |
+
size 84893
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:7bb6529dd627e6504e58db739debc71511c278501c9d275011c605729153d5f3
|
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-5.4.0-70-generic-x86_64-with-debian-buster-sid #78~18.04.1-Ubuntu SMP Sat Mar 20 14:10:07 UTC 2021
|
2 |
+
Python: 3.6.15
|
3 |
+
Stable-Baselines3: 1.3.0
|
4 |
+
PyTorch: 1.10.2+cu102
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.19.5
|
7 |
+
Gym: 0.19.0
|
replay.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2b072e9ba5a188c8ecbfe24f9254b2a94e13782fc98cdcb713df288d01b5aa6c
|
3 |
+
size 251979
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 281.3546656459137, "std_reward": 15.306895040442264, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-07T09:00:29.619744"}
|