bsmith0430
commited on
Commit
·
2b58a33
1
Parent(s):
8bf46b1
Upload PPO LunarLander-v2 trained agent
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: 280.99 +/- 13.02
|
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 0x7f99020f1710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f99020f17a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f99020f1830>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f99020f18c0>", "_build": "<function ActorCriticPolicy._build at 0x7f99020f1950>", "forward": "<function ActorCriticPolicy.forward at 0x7f99020f19e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f99020f1a70>", "_predict": "<function ActorCriticPolicy._predict at 0x7f99020f1b00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f99020f1b90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f99020f1c20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f99020f1cb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f99020c5300>"}, "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": 1669020988598046604, "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": 496, "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-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+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 sha256:747be7d96a6aee679081fc5edee3fa2df4cfb5f5702fdeb281bb8fac73e7823e
|
3 |
+
size 147048
|
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 0x7f99020f1710>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f99020f17a0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f99020f1830>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f99020f18c0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f99020f1950>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f99020f19e0>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f99020f1a70>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f99020f1b00>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f99020f1b90>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f99020f1c20>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f99020f1cb0>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f99020c5300>"
|
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": 1669020988598046604,
|
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:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAABr+U75bwmU/2Lj2POE+374gEZG+fcs2PgAAAAAAAAAAAP9APfLSIT5sXEi+N42wvpK5A76Du7w8AAAAAAAAAADNpna84ZCEuhtNsrUJsOqvtQ3QuVK+7zQAAIA/AACAPzNkQ70UoJS6KYm2tHZrCLBg6aS2NS5jMwAAgD8AAIA/wK+/vezQl7uT1L27qxskPRejrbzgZ1a6AAAAAAAAgD9NMwO9SK+PujEbszN0yDAwlK3gOkPSvLMAAIA/AACAPyDgdL76QEs/a3D5PY558b7ce9i+GSdFPgAAAAAAAAAA2v3TPYOIrz8GQp0+0LL1vn+HLD6YENs9AAAAAAAAAAANXds9RP5rPqLNSL7cvqC+wKQsvVXpj7wAAAAAAAAAAM3g0LzBDJ68Htd6PRoIb71hfEG9VfGlvgAAgD8AAIA/5lkLPqQ5uT/PuxI/Gw9Evjd2ID6W5NU+AAAAAAAAAABNCta92icYP1cjvT2x3ea+1wb1vD0aXD0AAAAAAAAAALNXc71I9626TaqyuhyOfjkP9H+6FTgBOQAAAAAAAAAAmiFOvlRygj94G4i++dLsviZHyb7KSbO9AAAAAAAAAACaRq+8SO+XuqJPnLt8VI08kIkGPNXKdb0AAIA/AACAPzO7/LxxLE27chmavTVMn77fenG9qzXPPgAAgD8AAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
|
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": 496,
|
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:b2c42a947ba0e6beecd38743d92d0d1e8a14e6352cf57f7016365a75c61dfbcb
|
3 |
+
size 87865
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9bafdbda04093ccf3ac757e1c54f6a627775049bbede9b43e96bd6fc38ee2924
|
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-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022
|
2 |
+
Python: 3.7.15
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.12.1+cu113
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.21.6
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (230 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 280.9942239210574, "std_reward": 13.019342842627873, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-11-21T09:08:33.754228"}
|