Upload Unit 1 AGENT - PPO LunarLander-v2
Browse files- .gitattributes +1 -0
- README.md +28 -0
- config.json +1 -0
- replay.mp4 +3 -0
- results.json +1 -0
- suo-lander-v1.zip +3 -0
- suo-lander-v1/_stable_baselines3_version +1 -0
- suo-lander-v1/data +94 -0
- suo-lander-v1/policy.optimizer.pth +3 -0
- suo-lander-v1/policy.pth +3 -0
- suo-lander-v1/pytorch_variables.pth +3 -0
- suo-lander-v1/system_info.txt +7 -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: 190.58 +/- 23.40
|
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 0x7f0363dcadd0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0363dcae60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0363dcaef0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0363dcaf80>", "_build": "<function ActorCriticPolicy._build at 0x7f0363dd2050>", "forward": "<function ActorCriticPolicy.forward at 0x7f0363dd20e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0363dd2170>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0363dd2200>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0363dd2290>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0363dd2320>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0363dd23b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0363da14b0>"}, "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": 557056, "_total_timesteps": 550000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651942108.2484584, "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": -0.012829090909090901, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 136, "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"}}
|
replay.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3b93ab42520eb210be598f483511d0d1bcb6aba598bef911fa3943f372efb531
|
3 |
+
size 251221
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 190.57634553739635, "std_reward": 23.39599543441546, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-07T17:47:56.154169"}
|
suo-lander-v1.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a69676849177921a3116131839473218fb306fe354ae6df2830a3bf910e67e56
|
3 |
+
size 144044
|
suo-lander-v1/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.5.0
|
suo-lander-v1/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 0x7f0363dcadd0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0363dcae60>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0363dcaef0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0363dcaf80>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f0363dd2050>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f0363dd20e0>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0363dd2170>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f0363dd2200>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0363dd2290>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0363dd2320>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0363dd23b0>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f0363da14b0>"
|
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": 557056,
|
46 |
+
"_total_timesteps": 550000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1651942108.2484584,
|
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": -0.012829090909090901,
|
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": 136,
|
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 |
+
}
|
suo-lander-v1/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:59e1a4bce8a729044d63bfbb7090ce507ab252ec317055f13d64970e453f2f2f
|
3 |
+
size 84829
|
suo-lander-v1/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5694d1731bb151436f29ece1f8fb10943ea02e0fa7d7575b2365c2cfeb121c35
|
3 |
+
size 43201
|
suo-lander-v1/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
suo-lander-v1/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
|