Danielmartinez
commited on
Commit
•
cd8c6c3
1
Parent(s):
58a6d42
first_attempt
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: 260.98 +/- 15.02
|
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 0x7f2d18df2160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2d18df21f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2d18df2280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2d18df2310>", "_build": "<function ActorCriticPolicy._build at 0x7f2d18df23a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f2d18df2430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2d18df24c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2d18df2550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2d18df25e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2d18df2670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2d18df2700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2d18ded5d0>"}, "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": 1670380935644713629, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAABAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": "3.8.15", "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 sha256:710d4ef1a3b3b72f855b2fb55cee9524edccb085547e4598fe5d82d17710e694
|
3 |
+
size 147150
|
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 0x7f2d18df2160>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2d18df21f0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2d18df2280>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2d18df2310>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f2d18df23a0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f2d18df2430>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2d18df24c0>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f2d18df2550>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2d18df25e0>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2d18df2670>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2d18df2700>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f2d18ded5d0>"
|
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": 1670380935644713629,
|
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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAABAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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 sha256:678d4de606e33d3e3e9c0e856333e93778f0edd9050c6de0f268336c9895cb19
|
3 |
+
size 87865
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0584f41e5909bf8c79f6cce663a75117dfbc32b19562b3ea05416e0f7ee2a9ab
|
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: 3.8.15
|
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 (196 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 260.9779023452888, "std_reward": 15.01876639958356, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-07T03:15:21.112308"}
|