micheljperez
commited on
Commit
•
cfb4d3a
1
Parent(s):
9a7b106
Upload PPO LunarLander-v2 trained agent. New Course RL 2.0
Browse files- README.md +20 -11
- config.json +1 -1
- ppo-LunarLander-v2.zip +2 -2
- ppo-LunarLander-v2/_stable_baselines3_version +1 -1
- ppo-LunarLander-v2/data +26 -25
- ppo-LunarLander-v2/policy.optimizer.pth +2 -2
- ppo-LunarLander-v2/policy.pth +2 -2
- ppo-LunarLander-v2/system_info.txt +7 -7
- replay.mp4 +2 -2
- results.json +1 -1
README.md
CHANGED
@@ -8,21 +8,30 @@ tags:
|
|
8 |
model-index:
|
9 |
- name: PPO
|
10 |
results:
|
11 |
-
-
|
12 |
-
- type: mean_reward
|
13 |
-
value: 299.23 +/- 10.04
|
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 |
-
|
24 |
-
|
25 |
-
|
26 |
-
|
27 |
-
|
28 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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: 247.61 +/- 14.87
|
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
CHANGED
@@ -1 +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 0x7f958973c950>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f958973c9e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f958973ca70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f958973cb00>", "_build": "<function ActorCriticPolicy._build at 0x7f958973cb90>", "forward": "<function ActorCriticPolicy.forward at 0x7f958973cc20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f958973ccb0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f958973cd40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f958973cdd0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f958973ce60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f958973cef0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f958977ec60>"}, "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": 5013504, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652477299.0064783, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJqJsbvDsUS6hhAHtFZA2y7v12c3qaSzMwAAgD8AAIA/I72APoztCz8E4JO9V6Qiv5iVtz4eaVu+AAAAAAAAAADNIcK8hyrePkJhcj10qSW/vUYtvWskWj0AAAAAAAAAAJpotzzv9r0/HzWDPc1DVr4auRc9MwrjPQAAAAAAAAAAZoKKPMMRdbp9yOy3iTLdskgoX7sihQo3AACAPwAAgD/NDrS88SS+Pz5tU74nWFg+nMfovGj6yb0AAAAAAAAAAIBEMj46qaY/r9YZP1+/B7/Ep5s+HRd/PgAAAAAAAAAAoD01vq/knD9jVA+/lZ8Rv6zgm75+DKK+AAAAAAAAAABDEfs+vHwFvi80DL33/8k7niIrvq3BE7wAAAAAAAAAADPTAbzUIJ+8ptVbvQ/oZz3XIHQ94XKmuwAAgD8AAIA/zdbxPPYkErqVjZY6dO5zttQg3bkGLrG5AAAAAAAAAACaM388j15sujDzkbOD8XKvH8DiOSuftzMAAIA/AACAP0bPDz436Es/iwDTPQ2DR79CLI8+yhEfPAAAAAAAAAAAZqBDPD1TT7sSWdq90PkGPH1GVjymfPK8AACAPwAAgD8a82G9r60rP63jb72DyFO/FnewvblyEL0AAAAAAAAAAGaunT6LFSU/DaAPPWrfI78lCwo//iV2vQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3920, "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": 256, "n_epochs": 8, "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"}}
|
|
|
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 0x7fd176a39d30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd176a39dc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd176a39e50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd176a39ee0>", "_build": "<function ActorCriticPolicy._build at 0x7fd176a39f70>", "forward": "<function ActorCriticPolicy.forward at 0x7fd176a3e040>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd176a3e0d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd176a3e160>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd176a3e1f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd176a3e280>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd176a3e310>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd176a3e3a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fd176a36db0>"}, "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": 1677267421013883132, "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": 1, "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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3ca43c5407a0b1b38ad41acb4256d5932334ffcfb90b51cc9c4ef0904fde2a6d
|
3 |
+
size 147408
|
ppo-LunarLander-v2/_stable_baselines3_version
CHANGED
@@ -1 +1 @@
|
|
1 |
-
1.
|
|
|
1 |
+
1.7.0
|
ppo-LunarLander-v2/data
CHANGED
@@ -3,20 +3,21 @@
|
|
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
|
7 |
-
"__init__": "<function ActorCriticPolicy.__init__ at
|
8 |
-
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at
|
9 |
-
"reset_noise": "<function ActorCriticPolicy.reset_noise at
|
10 |
-
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at
|
11 |
-
"_build": "<function ActorCriticPolicy._build at
|
12 |
-
"forward": "<function ActorCriticPolicy.forward at
|
13 |
-
"
|
14 |
-
"
|
15 |
-
"
|
16 |
-
"
|
17 |
-
"
|
|
|
18 |
"__abstractmethods__": "frozenset()",
|
19 |
-
"_abc_impl": "<_abc_data object at
|
20 |
},
|
21 |
"verbose": 1,
|
22 |
"policy_kwargs": {},
|
@@ -42,21 +43,21 @@
|
|
42 |
"_np_random": null
|
43 |
},
|
44 |
"n_envs": 16,
|
45 |
-
"num_timesteps":
|
46 |
-
"_total_timesteps":
|
47 |
"_num_timesteps_at_start": 0,
|
48 |
"seed": null,
|
49 |
"action_noise": null,
|
50 |
-
"start_time":
|
51 |
"learning_rate": 0.0003,
|
52 |
"tensorboard_log": null,
|
53 |
"lr_schedule": {
|
54 |
":type:": "<class 'function'>",
|
55 |
-
":serialized:": "
|
56 |
},
|
57 |
"_last_obs": {
|
58 |
":type:": "<class 'numpy.ndarray'>",
|
59 |
-
":serialized:": "
|
60 |
},
|
61 |
"_last_episode_starts": {
|
62 |
":type:": "<class 'numpy.ndarray'>",
|
@@ -66,27 +67,27 @@
|
|
66 |
"_episode_num": 0,
|
67 |
"use_sde": false,
|
68 |
"sde_sample_freq": -1,
|
69 |
-
"_current_progress_remaining": -0.
|
70 |
"ep_info_buffer": {
|
71 |
":type:": "<class 'collections.deque'>",
|
72 |
-
":serialized:": "
|
73 |
},
|
74 |
"ep_success_buffer": {
|
75 |
":type:": "<class 'collections.deque'>",
|
76 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
77 |
},
|
78 |
-
"_n_updates":
|
79 |
"n_steps": 1024,
|
80 |
-
"gamma":
|
81 |
"gae_lambda": 0.98,
|
82 |
"ent_coef": 0.01,
|
83 |
"vf_coef": 0.5,
|
84 |
"max_grad_norm": 0.5,
|
85 |
-
"batch_size":
|
86 |
-
"n_epochs":
|
87 |
"clip_range": {
|
88 |
":type:": "<class 'function'>",
|
89 |
-
":serialized:": "
|
90 |
},
|
91 |
"clip_range_vf": null,
|
92 |
"normalize_advantage": true,
|
|
|
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 0x7fd176a39d30>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd176a39dc0>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd176a39e50>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd176a39ee0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fd176a39f70>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fd176a3e040>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd176a3e0d0>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd176a3e160>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fd176a3e1f0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd176a3e280>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd176a3e310>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd176a3e3a0>",
|
19 |
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc_data object at 0x7fd176a36db0>"
|
21 |
},
|
22 |
"verbose": 1,
|
23 |
"policy_kwargs": {},
|
|
|
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": 1677267421013883132,
|
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'>",
|
|
|
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": 1,
|
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,
|
ppo-LunarLander-v2/policy.optimizer.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f9234268474d1abdc832d508f9338d52baca2c149faceeb657343f2d108fe94f
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:eebd144bfe05d22a64196a918f8828456942130dcd4b9e1f4929ea14a897c30f
|
3 |
+
size 43393
|
ppo-LunarLander-v2/system_info.txt
CHANGED
@@ -1,7 +1,7 @@
|
|
1 |
-
OS: Linux-5.
|
2 |
-
Python: 3.
|
3 |
-
Stable-Baselines3: 1.
|
4 |
-
PyTorch: 1.
|
5 |
-
GPU Enabled: True
|
6 |
-
Numpy: 1.
|
7 |
-
Gym: 0.21.0
|
|
|
1 |
+
- OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.8.10
|
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
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9af876257dc7dd29f24e48ccafcf6026c46b165bf6e0415d7a999d3efcae9b20
|
3 |
+
size 190307
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 247.61437307988453, "std_reward": 14.874217791666013, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-24T20:18:37.516803"}
|