Commit
·
1b3bf45
1
Parent(s):
6f2aa16
first PPO algorithm
Browse files- README.md +37 -0
- config.json +1 -0
- replay.mp4 +0 -0
- results.json +1 -0
- zarifPPO.zip +3 -0
- zarifPPO/_stable_baselines3_version +1 -0
- zarifPPO/data +95 -0
- zarifPPO/policy.optimizer.pth +3 -0
- zarifPPO/policy.pth +3 -0
- zarifPPO/pytorch_variables.pth +3 -0
- zarifPPO/system_info.txt +7 -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: 241.08 +/- 16.60
|
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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f872ec5b550>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f872ec5b5e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f872ec5b670>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f872ec5b700>", "_build": "<function ActorCriticPolicy._build at 0x7f872ec5b790>", "forward": "<function ActorCriticPolicy.forward at 0x7f872ec5b820>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f872ec5b8b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f872ec5b940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f872ec5b9d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f872ec5ba60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f872ec5baf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f872ec5bb80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f872ec5c5c0>"}, "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": 1678556758846415648, "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-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
replay.mp4
ADDED
Binary file (237 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 241.08288577585034, "std_reward": 16.60199617654579, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-11T18:10:47.291463"}
|
zarifPPO.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:00845d94cea923b1fc239465fb7acfd4a05c7cbf037ce0a6bb5c695d22555ef8
|
3 |
+
size 147429
|
zarifPPO/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
zarifPPO/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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f872ec5b550>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f872ec5b5e0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f872ec5b670>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f872ec5b700>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f872ec5b790>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f872ec5b820>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f872ec5b8b0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f872ec5b940>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f872ec5b9d0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f872ec5ba60>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f872ec5baf0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f872ec5bb80>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f872ec5c5c0>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"observation_space": {
|
25 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
26 |
+
":serialized:": "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",
|
27 |
+
"dtype": "float32",
|
28 |
+
"_shape": [
|
29 |
+
8
|
30 |
+
],
|
31 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
32 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
33 |
+
"bounded_below": "[False False False False False False False False]",
|
34 |
+
"bounded_above": "[False False False False False False False False]",
|
35 |
+
"_np_random": null
|
36 |
+
},
|
37 |
+
"action_space": {
|
38 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
39 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
40 |
+
"n": 4,
|
41 |
+
"_shape": [],
|
42 |
+
"dtype": "int64",
|
43 |
+
"_np_random": null
|
44 |
+
},
|
45 |
+
"n_envs": 16,
|
46 |
+
"num_timesteps": 1015808,
|
47 |
+
"_total_timesteps": 1000000,
|
48 |
+
"_num_timesteps_at_start": 0,
|
49 |
+
"seed": null,
|
50 |
+
"action_noise": null,
|
51 |
+
"start_time": 1678556758846415648,
|
52 |
+
"learning_rate": 0.0003,
|
53 |
+
"tensorboard_log": null,
|
54 |
+
"lr_schedule": {
|
55 |
+
":type:": "<class 'function'>",
|
56 |
+
":serialized:": "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"
|
57 |
+
},
|
58 |
+
"_last_obs": {
|
59 |
+
":type:": "<class 'numpy.ndarray'>",
|
60 |
+
":serialized:": "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"
|
61 |
+
},
|
62 |
+
"_last_episode_starts": {
|
63 |
+
":type:": "<class 'numpy.ndarray'>",
|
64 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
65 |
+
},
|
66 |
+
"_last_original_obs": null,
|
67 |
+
"_episode_num": 0,
|
68 |
+
"use_sde": false,
|
69 |
+
"sde_sample_freq": -1,
|
70 |
+
"_current_progress_remaining": -0.015808000000000044,
|
71 |
+
"ep_info_buffer": {
|
72 |
+
":type:": "<class 'collections.deque'>",
|
73 |
+
":serialized:": "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"
|
74 |
+
},
|
75 |
+
"ep_success_buffer": {
|
76 |
+
":type:": "<class 'collections.deque'>",
|
77 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
78 |
+
},
|
79 |
+
"_n_updates": 248,
|
80 |
+
"n_steps": 1024,
|
81 |
+
"gamma": 0.999,
|
82 |
+
"gae_lambda": 0.98,
|
83 |
+
"ent_coef": 0.01,
|
84 |
+
"vf_coef": 0.5,
|
85 |
+
"max_grad_norm": 0.5,
|
86 |
+
"batch_size": 64,
|
87 |
+
"n_epochs": 4,
|
88 |
+
"clip_range": {
|
89 |
+
":type:": "<class 'function'>",
|
90 |
+
":serialized:": "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"
|
91 |
+
},
|
92 |
+
"clip_range_vf": null,
|
93 |
+
"normalize_advantage": true,
|
94 |
+
"target_kl": null
|
95 |
+
}
|
zarifPPO/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0f2600db256ef3781f5c88a3e574f113edad983a6d55da14b474f913b339c684
|
3 |
+
size 87929
|
zarifPPO/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:424d62909b87c99cc7cfe1eebf234759b50f3e13cc2c5ba5ab4b0af9ec1027ff
|
3 |
+
size 43393
|
zarifPPO/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
zarifPPO/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.9.16
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
+
- PyTorch: 1.13.1+cu116
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.22.4
|
7 |
+
- Gym: 0.21.0
|