Initial commit
Browse files- README.md +37 -0
- config.json +1 -0
- ppo.zip +3 -0
- ppo/_stable_baselines3_version +1 -0
- ppo/data +95 -0
- ppo/policy.optimizer.pth +3 -0
- ppo/policy.pth +3 -0
- ppo/pytorch_variables.pth +3 -0
- ppo/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: 257.45 +/- 22.19
|
| 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 0x7f35308a8940>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f35308a89d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f35308a8a60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f35308a8af0>", "_build": "<function ActorCriticPolicy._build at 0x7f35308a8b80>", "forward": "<function ActorCriticPolicy.forward at 0x7f35308a8c10>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f35308a8ca0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f35308a8d30>", "_predict": "<function ActorCriticPolicy._predict at 0x7f35308a8dc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f35308a8e50>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f35308a8ee0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f35308a8f70>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f35308aa640>"}, "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": 1679383638029561964, "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": 310, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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"}}
|
ppo.zip
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:de7ab44efd66a0553ec6143f92a373c30d80b2ac997b274ca9f47685b09a250f
|
| 3 |
+
size 147344
|
ppo/_stable_baselines3_version
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1.7.0
|
ppo/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 0x7f35308a8940>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f35308a89d0>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f35308a8a60>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f35308a8af0>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f35308a8b80>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f35308a8c10>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f35308a8ca0>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f35308a8d30>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f35308a8dc0>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f35308a8e50>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f35308a8ee0>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f35308a8f70>",
|
| 19 |
+
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f35308aa640>"
|
| 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": 1679383638029561964,
|
| 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": 310,
|
| 80 |
+
"n_steps": 2048,
|
| 81 |
+
"gamma": 0.99,
|
| 82 |
+
"gae_lambda": 0.95,
|
| 83 |
+
"ent_coef": 0.0,
|
| 84 |
+
"vf_coef": 0.5,
|
| 85 |
+
"max_grad_norm": 0.5,
|
| 86 |
+
"batch_size": 64,
|
| 87 |
+
"n_epochs": 10,
|
| 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 |
+
}
|
ppo/policy.optimizer.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:17fb1ac015fa6b2c46f640a662c3d12c6278350ed0c872ef2e90ad76072e0e34
|
| 3 |
+
size 87929
|
ppo/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b738c64dea58c9888b0eb20695f265a6b0933cd5d5ed0faa074f23466263a2b4
|
| 3 |
+
size 43393
|
ppo/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/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
|
replay.mp4
ADDED
|
Binary file (149 kB). View file
|
|
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 257.44663735887104, "std_reward": 22.19376159571918, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-21T07:59:11.093173"}
|