PPO training on LunarLander-v2
Browse files- README.md +1 -1
- config.json +1 -1
- lunarlander_ppo_1e6.zip +2 -2
- lunarlander_ppo_1e6/_stable_baselines3_version +1 -1
- lunarlander_ppo_1e6/data +39 -36
- lunarlander_ppo_1e6/policy.optimizer.pth +1 -1
- lunarlander_ppo_1e6/policy.pth +1 -1
- lunarlander_ppo_1e6/system_info.txt +7 -5
- replay.mp4 +0 -0
- results.json +1 -1
README.md
CHANGED
@@ -16,7 +16,7 @@ model-index:
|
|
16 |
type: LunarLander-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
-
value:
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
|
|
16 |
type: LunarLander-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
+
value: 271.79 +/- 22.81
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
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 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 0x7f59eb0c2310>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f59eb0c23a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f59eb0c2430>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f59eb0c24c0>", "_build": "<function ActorCriticPolicy._build at 0x7f59eb0c2550>", "forward": "<function ActorCriticPolicy.forward at 0x7f59eb0c25e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f59eb0c2670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f59eb0c2700>", "_predict": "<function ActorCriticPolicy._predict at 0x7f59eb0c2790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f59eb0c2820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f59eb0c28b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f59eb0c2940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f59eb0c39c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1682288637349961830, "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, "_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": 310, "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, "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": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "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 0x7f1f08807eb0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1f08807f40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1f0880c040>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1f0880c0d0>", "_build": "<function ActorCriticPolicy._build at 0x7f1f0880c160>", "forward": "<function ActorCriticPolicy.forward at 0x7f1f0880c1f0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f1f0880c280>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1f0880c310>", "_predict": "<function ActorCriticPolicy._predict at 0x7f1f0880c3a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1f0880c430>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1f0880c4c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1f0880c550>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f1f08808d00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1684600165461357504, "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": 620, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "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": 10, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
lunarlander_ppo_1e6.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 sha256:1eaa910f0ba87d370132c6a881ec6ca05eebac236b498032e3db2adbe53925ae
|
3 |
+
size 146656
|
lunarlander_ppo_1e6/_stable_baselines3_version
CHANGED
@@ -1 +1 @@
|
|
1 |
-
|
|
|
1 |
+
2.0.0a5
|
lunarlander_ppo_1e6/data
CHANGED
@@ -4,20 +4,20 @@
|
|
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
|
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 |
-
"extract_features": "<function ActorCriticPolicy.extract_features at
|
14 |
-
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at
|
15 |
-
"_predict": "<function ActorCriticPolicy._predict at
|
16 |
-
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at
|
17 |
-
"get_distribution": "<function ActorCriticPolicy.get_distribution at
|
18 |
-
"predict_values": "<function ActorCriticPolicy.predict_values at
|
19 |
"__abstractmethods__": "frozenset()",
|
20 |
-
"_abc_impl": "<_abc._abc_data object at
|
21 |
},
|
22 |
"verbose": 1,
|
23 |
"policy_kwargs": {},
|
@@ -26,16 +26,12 @@
|
|
26 |
"_num_timesteps_at_start": 0,
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
-
"start_time":
|
30 |
"learning_rate": 0.0003,
|
31 |
"tensorboard_log": null,
|
32 |
-
"lr_schedule": {
|
33 |
-
":type:": "<class 'function'>",
|
34 |
-
":serialized:": "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"
|
35 |
-
},
|
36 |
"_last_obs": {
|
37 |
":type:": "<class 'numpy.ndarray'>",
|
38 |
-
":serialized:": "
|
39 |
},
|
40 |
"_last_episode_starts": {
|
41 |
":type:": "<class 'numpy.ndarray'>",
|
@@ -49,48 +45,55 @@
|
|
49 |
"_stats_window_size": 100,
|
50 |
"ep_info_buffer": {
|
51 |
":type:": "<class 'collections.deque'>",
|
52 |
-
":serialized:": "
|
53 |
},
|
54 |
"ep_success_buffer": {
|
55 |
":type:": "<class 'collections.deque'>",
|
56 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
57 |
},
|
58 |
-
"_n_updates":
|
59 |
"observation_space": {
|
60 |
-
":type:": "<class '
|
61 |
-
":serialized:": "
|
62 |
"dtype": "float32",
|
|
|
|
|
63 |
"_shape": [
|
64 |
8
|
65 |
],
|
66 |
-
"low": "[-
|
67 |
-
"high": "[
|
68 |
-
"
|
69 |
-
"
|
70 |
"_np_random": null
|
71 |
},
|
72 |
"action_space": {
|
73 |
-
":type:": "<class '
|
74 |
-
":serialized:": "
|
75 |
-
"n": 4,
|
|
|
76 |
"_shape": [],
|
77 |
"dtype": "int64",
|
78 |
"_np_random": null
|
79 |
},
|
80 |
"n_envs": 16,
|
81 |
-
"n_steps":
|
82 |
-
"gamma": 0.
|
83 |
-
"gae_lambda": 0.
|
84 |
-
"ent_coef": 0.
|
85 |
"vf_coef": 0.5,
|
86 |
"max_grad_norm": 0.5,
|
87 |
"batch_size": 64,
|
88 |
"n_epochs": 10,
|
89 |
"clip_range": {
|
90 |
":type:": "<class 'function'>",
|
91 |
-
":serialized:": "
|
92 |
},
|
93 |
"clip_range_vf": null,
|
94 |
"normalize_advantage": true,
|
95 |
-
"target_kl": null
|
|
|
|
|
|
|
|
|
96 |
}
|
|
|
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 0x7f1f08807eb0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1f08807f40>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1f0880c040>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1f0880c0d0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f1f0880c160>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f1f0880c1f0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f1f0880c280>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1f0880c310>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f1f0880c3a0>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1f0880c430>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1f0880c4c0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1f0880c550>",
|
19 |
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f1f08808d00>"
|
21 |
},
|
22 |
"verbose": 1,
|
23 |
"policy_kwargs": {},
|
|
|
26 |
"_num_timesteps_at_start": 0,
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
+
"start_time": 1684600165461357504,
|
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'>",
|
|
|
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": 620,
|
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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
"_shape": [],
|
76 |
"dtype": "int64",
|
77 |
"_np_random": null
|
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": 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 |
+
"lr_schedule": {
|
96 |
+
":type:": "<class 'function'>",
|
97 |
+
":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
|
98 |
+
}
|
99 |
}
|
lunarlander_ppo_1e6/policy.optimizer.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 87929
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:efb480b4d5c5919077ac7db95ce4af1bbbeb7f4c470116d74ef09f19c10e0da9
|
3 |
size 87929
|
lunarlander_ppo_1e6/policy.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 43329
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:67516f7dea4cd5ec92d2eeac5eefa9c5bc2bac6f1fe3be911210c883fc5f4ec6
|
3 |
size 43329
|
lunarlander_ppo_1e6/system_info.txt
CHANGED
@@ -1,7 +1,9 @@
|
|
1 |
-
- OS: Linux-5.
|
2 |
-
- Python: 3.
|
3 |
-
- Stable-Baselines3:
|
4 |
-
- PyTorch: 2.0.
|
5 |
- GPU Enabled: True
|
6 |
- Numpy: 1.22.4
|
7 |
-
-
|
|
|
|
|
|
1 |
+
- OS: Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
|
2 |
+
- Python: 3.10.11
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.0.1+cu118
|
5 |
- GPU Enabled: True
|
6 |
- Numpy: 1.22.4
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 271.79469734225995, "std_reward": 22.807300509658074, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-20T16:57:09.406713"}
|