Please kill me
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 +99 -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 +9 -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: 257.94 +/- 17.21
|
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 0x7cac48814a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cac48814af0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cac48814b80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cac48814c10>", "_build": "<function ActorCriticPolicy._build at 0x7cac48814ca0>", "forward": "<function ActorCriticPolicy.forward at 0x7cac48814d30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7cac48814dc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cac48814e50>", "_predict": "<function ActorCriticPolicy._predict at 0x7cac48814ee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cac48814f70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cac48815000>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7cac48815090>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cac48818580>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710518930015503199, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 284, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8dc4f97c6c92171a50fc7d78f0c4138787567c458271d237ff6388715fe061f5
|
3 |
+
size 148362
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,99 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7cac48814a60>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cac48814af0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cac48814b80>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cac48814c10>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7cac48814ca0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7cac48814d30>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7cac48814dc0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cac48814e50>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7cac48814ee0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cac48814f70>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cac48815000>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7cac48815090>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7cac48818580>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1015808,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1710518930015503199,
|
30 |
+
"learning_rate": 0.0003,
|
31 |
+
"tensorboard_log": null,
|
32 |
+
"_last_obs": {
|
33 |
+
":type:": "<class 'numpy.ndarray'>",
|
34 |
+
":serialized:": "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"
|
35 |
+
},
|
36 |
+
"_last_episode_starts": {
|
37 |
+
":type:": "<class 'numpy.ndarray'>",
|
38 |
+
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
39 |
+
},
|
40 |
+
"_last_original_obs": null,
|
41 |
+
"_episode_num": 0,
|
42 |
+
"use_sde": false,
|
43 |
+
"sde_sample_freq": -1,
|
44 |
+
"_current_progress_remaining": -0.015808000000000044,
|
45 |
+
"_stats_window_size": 100,
|
46 |
+
"ep_info_buffer": {
|
47 |
+
":type:": "<class 'collections.deque'>",
|
48 |
+
":serialized:": "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"
|
49 |
+
},
|
50 |
+
"ep_success_buffer": {
|
51 |
+
":type:": "<class 'collections.deque'>",
|
52 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
+
},
|
54 |
+
"_n_updates": 284,
|
55 |
+
"observation_space": {
|
56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
+
":serialized:": "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",
|
58 |
+
"dtype": "float32",
|
59 |
+
"bounded_below": "[ True True True True True True True True]",
|
60 |
+
"bounded_above": "[ True True True True True True True True]",
|
61 |
+
"_shape": [
|
62 |
+
8
|
63 |
+
],
|
64 |
+
"low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
65 |
+
"high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
66 |
+
"low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
|
67 |
+
"high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
|
68 |
+
"_np_random": null
|
69 |
+
},
|
70 |
+
"action_space": {
|
71 |
+
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
72 |
+
":serialized:": "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",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": "Generator(PCG64)"
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
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 |
+
"lr_schedule": {
|
96 |
+
":type:": "<class 'function'>",
|
97 |
+
":serialized:": "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"
|
98 |
+
}
|
99 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4d47b88d6087d4982ee28c778fe6603f0efcbad01288e1b900b257ac13642de6
|
3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b4aad83e934c8de689583c4f7982857589ebc341a57e5a4fa9ec5257eb7bb745
|
3 |
+
size 43762
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
|
3 |
+
size 864
|
ppo-LunarLander-v2/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.2.1+cu121
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.25.2
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (185 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 257.93837879999995, "std_reward": 17.213709919356866, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-15T16:38:13.795116"}
|