Commit
•
19c253b
1
Parent(s):
5ef9363
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: 252.93 +/- 21.79
|
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 0x00000218AC1B6B90>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x00000218AC1B6C20>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x00000218AC1B6CB0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x00000218AC1B6D40>", "_build": "<function ActorCriticPolicy._build at 0x00000218AC1B6DD0>", "forward": "<function ActorCriticPolicy.forward at 0x00000218AC1B6E60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x00000218AC1B6EF0>", "_predict": "<function ActorCriticPolicy._predict at 0x00000218AC1B6F80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x00000218AC1B7010>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x00000218AC1B70A0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x00000218AC1B7130>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x00000218AC1B2BC0>"}, "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:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670730029205730400, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAMb4az7zXYw/h52NPsTPg77CgjM+Ok7FPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3908, "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": "Windows-10-10.0.22621-SP0 10.0.22621", "Python": "3.10.6", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu117", "GPU Enabled": "True", "Numpy": "1.23.4", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:98143dd31370913e758919586b5ff6545133552bc54b650c861183c4c7b41f53
|
3 |
+
size 146596
|
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 0x00000218AC1B6B90>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x00000218AC1B6C20>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x00000218AC1B6CB0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x00000218AC1B6D40>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x00000218AC1B6DD0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x00000218AC1B6E60>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x00000218AC1B6EF0>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x00000218AC1B6F80>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x00000218AC1B7010>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x00000218AC1B70A0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x00000218AC1B7130>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc._abc_data object at 0x00000218AC1B2BC0>"
|
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:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
39 |
+
"n": 4,
|
40 |
+
"_shape": [],
|
41 |
+
"dtype": "int64",
|
42 |
+
"_np_random": null
|
43 |
+
},
|
44 |
+
"n_envs": 1,
|
45 |
+
"num_timesteps": 1000448,
|
46 |
+
"_total_timesteps": 1000000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1670730029205730400,
|
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:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAMb4az7zXYw/h52NPsTPg77CgjM+Ok7FPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
|
60 |
+
},
|
61 |
+
"_last_episode_starts": {
|
62 |
+
":type:": "<class 'numpy.ndarray'>",
|
63 |
+
":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
|
64 |
+
},
|
65 |
+
"_last_original_obs": null,
|
66 |
+
"_episode_num": 0,
|
67 |
+
"use_sde": false,
|
68 |
+
"sde_sample_freq": -1,
|
69 |
+
"_current_progress_remaining": -0.00044800000000000395,
|
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": 3908,
|
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 sha256:0c75b860e1a7abd77fc7a4d3e23bd8bce05f6dfa07830c36a5c7166a066f5a31
|
3 |
+
size 88057
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:99c57f9d48b7a13b90ae1773133fc83f9215a33f94aea92941ca875a538876e6
|
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: Windows-10-10.0.22621-SP0 10.0.22621
|
2 |
+
Python: 3.10.6
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.13.0+cu117
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.23.4
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (221 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 252.92800063857953, "std_reward": 21.788972339226845, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-11T11:52:49.147253"}
|