Push LunarLander-v2
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: 231.48 +/- 63.87
|
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 0x7f93335755e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9333575670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9333575700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9333575790>", "_build": "<function ActorCriticPolicy._build at 0x7f9333575820>", "forward": "<function ActorCriticPolicy.forward at 0x7f93335758b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9333575940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f93335759d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9333575a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9333575af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9333575b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f93335ece70>"}, "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": 1670601702745806616, "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": 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-5.10.133+-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 sha256:65cd0d06403be14d8ecd2d1de44616d6cfe1749b70daf55a2d173582f079c0ee
|
3 |
+
size 147214
|
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 0x7f93335755e0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9333575670>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9333575700>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9333575790>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f9333575820>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f93335758b0>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9333575940>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f93335759d0>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9333575a60>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9333575af0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9333575b80>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f93335ece70>"
|
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": 1670601702745806616,
|
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": 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:ef6421f83ac870e3b7a3fb6c69b392f8719eb4042a617c866418bfbe95cdfad6
|
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:cb3bbdd42a7bdb60afb6682f095c7ff9d4f44923d78af41dda13b37703ee17af
|
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 (205 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 231.48082778921267, "std_reward": 63.86600648067567, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-09T16:52:55.705232"}
|