Commit ·
a01cb69
1
Parent(s): d2853b3
Upload the very first RL model
Browse files- .gitattributes +1 -0
- README.md +28 -0
- config.json +1 -0
- ppo-LunarLander.zip +3 -0
- ppo-LunarLander/_stable_baselines3_version +1 -0
- ppo-LunarLander/data +94 -0
- ppo-LunarLander/policy.optimizer.pth +3 -0
- ppo-LunarLander/policy.pth +3 -0
- ppo-LunarLander/pytorch_variables.pth +3 -0
- ppo-LunarLander/system_info.txt +7 -0
- replay.mp4 +3 -0
- results.json +1 -0
.gitattributes
CHANGED
|
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 25 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 26 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
| 27 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 25 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 26 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
| 27 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 28 |
+
*.mp4 filter=lfs diff=lfs merge=lfs -text
|
README.md
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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 |
+
- metrics:
|
| 12 |
+
- type: mean_reward
|
| 13 |
+
value: 238.37 +/- 22.09
|
| 14 |
+
name: mean_reward
|
| 15 |
+
task:
|
| 16 |
+
type: reinforcement-learning
|
| 17 |
+
name: reinforcement-learning
|
| 18 |
+
dataset:
|
| 19 |
+
name: LunarLander-v2
|
| 20 |
+
type: LunarLander-v2
|
| 21 |
+
---
|
| 22 |
+
|
| 23 |
+
# **PPO** Agent playing **LunarLander-v2**
|
| 24 |
+
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
|
| 25 |
+
|
| 26 |
+
## Usage (with Stable-baselines3)
|
| 27 |
+
TODO: Add your code
|
| 28 |
+
|
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 0x7f4602dda9e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4602ddaa70>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4602ddab00>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4602ddab90>", "_build": "<function ActorCriticPolicy._build at 0x7f4602ddac20>", "forward": "<function ActorCriticPolicy.forward at 0x7f4602ddacb0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4602ddad40>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4602ddadd0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4602ddae60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4602ddaef0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4602ddaf80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f4602e26930>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652531587.551753, "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": 124, "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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
|
ppo-LunarLander.zip
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3d0236f0f48e6f74c3d03ad8e4241773f0494adc1e46a0bb73a84e44c7aebf79
|
| 3 |
+
size 144027
|
ppo-LunarLander/_stable_baselines3_version
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1.5.0
|
ppo-LunarLander/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 0x7f4602dda9e0>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4602ddaa70>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4602ddab00>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4602ddab90>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f4602ddac20>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f4602ddacb0>",
|
| 13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4602ddad40>",
|
| 14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f4602ddadd0>",
|
| 15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4602ddae60>",
|
| 16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4602ddaef0>",
|
| 17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4602ddaf80>",
|
| 18 |
+
"__abstractmethods__": "frozenset()",
|
| 19 |
+
"_abc_impl": "<_abc_data object at 0x7f4602e26930>"
|
| 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": 507904,
|
| 46 |
+
"_total_timesteps": 500000,
|
| 47 |
+
"_num_timesteps_at_start": 0,
|
| 48 |
+
"seed": null,
|
| 49 |
+
"action_noise": null,
|
| 50 |
+
"start_time": 1652531587.551753,
|
| 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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 124,
|
| 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/policy.optimizer.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6458212c4cb9b7379ead308d0da8a1316a3643956a7f8515c60d841622c02f9b
|
| 3 |
+
size 84829
|
ppo-LunarLander/policy.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:498c2c7abedde43c7d2b863849ea08d3e46ecb4e8c77a4c8625de01b59865f96
|
| 3 |
+
size 43201
|
ppo-LunarLander/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/system_info.txt
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
|
| 2 |
+
Python: 3.7.13
|
| 3 |
+
Stable-Baselines3: 1.5.0
|
| 4 |
+
PyTorch: 1.11.0+cu113
|
| 5 |
+
GPU Enabled: True
|
| 6 |
+
Numpy: 1.21.6
|
| 7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:31856186da56f0a90464b7994540d6bb4ad36fd802869f0fbccbe86416fb2f7b
|
| 3 |
+
size 162841
|
results.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"mean_reward": 238.36598823442415, "std_reward": 22.09241561160821, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-14T12:53:48.484771"}
|