Upload PPO LunarLander-v2 trained agent
Browse files- README.md +1 -1
- config.json +1 -1
- ppo-LunarLander-v2.zip +2 -2
- ppo-LunarLander-v2/_stable_baselines3_version +1 -1
- ppo-LunarLander-v2/data +49 -44
- ppo-LunarLander-v2/policy.optimizer.pth +2 -2
- ppo-LunarLander-v2/policy.pth +2 -2
- ppo-LunarLander-v2/pytorch_variables.pth +2 -2
- ppo-LunarLander-v2/system_info.txt +9 -7
- 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: 251.94 +/- 17.46
|
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 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 0x7f115d34bca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f115d34bd30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f115d34bdc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f115d34be50>", "_build": "<function ActorCriticPolicy._build at 0x7f115d34bee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f115d34bf70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f115d34f040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f115d34f0d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f115d34f160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f115d34f1f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f115d34f280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f115d3484b0>"}, "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": 1671527403705093556, "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": 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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "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 0x787eee9b35b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x787eee9b3640>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x787eee9b36d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x787eee9b3760>", "_build": "<function ActorCriticPolicy._build at 0x787eee9b37f0>", "forward": "<function ActorCriticPolicy.forward at 0x787eee9b3880>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x787eee9b3910>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x787eee9b39a0>", "_predict": "<function ActorCriticPolicy._predict at 0x787eee9b3a30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x787eee9b3ac0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x787eee9b3b50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x787eee9b3be0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x787eee9b8740>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1709977746012006357, "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": 248, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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": 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": "2.1.0+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
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 sha256:2c5939bed7bde270116463e789cde071891e044db80de7e63fdd76575b6d19ab
|
3 |
+
size 148084
|
ppo-LunarLander-v2/_stable_baselines3_version
CHANGED
@@ -1 +1 @@
|
|
1 |
-
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2/data
CHANGED
@@ -3,60 +3,35 @@
|
|
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": {},
|
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": 1015808,
|
46 |
"_total_timesteps": 1000000,
|
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:": "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"
|
56 |
-
},
|
57 |
"_last_obs": {
|
58 |
":type:": "<class 'numpy.ndarray'>",
|
59 |
-
":serialized:": "
|
60 |
},
|
61 |
"_last_episode_starts": {
|
62 |
":type:": "<class 'numpy.ndarray'>",
|
@@ -67,15 +42,41 @@
|
|
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:": "
|
73 |
},
|
74 |
"ep_success_buffer": {
|
75 |
":type:": "<class 'collections.deque'>",
|
76 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
77 |
},
|
78 |
"_n_updates": 248,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
79 |
"n_steps": 1024,
|
80 |
"gamma": 0.999,
|
81 |
"gae_lambda": 0.98,
|
@@ -86,9 +87,13 @@
|
|
86 |
"n_epochs": 4,
|
87 |
"clip_range": {
|
88 |
":type:": "<class 'function'>",
|
89 |
-
":serialized:": "
|
90 |
},
|
91 |
"clip_range_vf": null,
|
92 |
"normalize_advantage": true,
|
93 |
-
"target_kl": null
|
|
|
|
|
|
|
|
|
94 |
}
|
|
|
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 0x787eee9b35b0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x787eee9b3640>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x787eee9b36d0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x787eee9b3760>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x787eee9b37f0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x787eee9b3880>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x787eee9b3910>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x787eee9b39a0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x787eee9b3a30>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x787eee9b3ac0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x787eee9b3b50>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x787eee9b3be0>",
|
19 |
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x787eee9b8740>"
|
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": 1709977746012006357,
|
30 |
"learning_rate": 0.0003,
|
31 |
"tensorboard_log": null,
|
|
|
|
|
|
|
|
|
32 |
"_last_obs": {
|
33 |
":type:": "<class 'numpy.ndarray'>",
|
34 |
+
":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAANqHGz6Drgy8TpKFOyp5yLkea2m9ckGnugAAAAAAAIA/Ztz/vK5tjrouxBG1KkIksKfxgbp2QGE0AACAPwAAgD9zFcI91AaQPV4wJryA4Bq+q2YUPZ+eRL0AAAAAAAAAAHVblL4VTJw/yuDSvgaHur6O3rS+VzOHOwAAAAAAAAAAZiavO/KUJj7Os2097RxHvkGDkD0jODK9AAAAAAAAAACmGpa+mpdsP45Utr6Z96C+l+K8vjiK170AAAAAAAAAADpoC76xY5U/7V9SvgQvvL5o1Ci+3bkGvQAAAAAAAAAA08dOPkn9ST86skW+2ceXvh980rye0oK9AAAAAAAAAABmVP8873YpPXffJTzXnki+Kbt6vdW/uDwAAAAAAAAAABrwoD3r28Q9U/xvO/V9Ub6F6pq8I8hLvQAAAAAAAAAAxmhBPrZeeLw1NAs7PTJCuTzD1r2XyBy6AACAPwAAgD9zjY09/wxWP/NIZ70fu6m+0jvtPGm/hr0AAAAAAAAAAGbZwL3hnoW6Cy9hOsTvVjX62ws7ii2DuQAAgD8AAAAA02GHPkq8tj9JoSw/9fDbvoIsxj6bN2Q+AAAAAAAAAAANaZ+9HBO2P2an5b6btQO+zfIPvUXmV74AAAAAAAAAAE1r3r0UWIW6K3V6utERa7UgBvm5P/mROQAAgD8AAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
|
35 |
},
|
36 |
"_last_episode_starts": {
|
37 |
":type:": "<class 'numpy.ndarray'>",
|
|
|
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": 248,
|
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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
|
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,
|
|
|
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
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:c4bf43543f47cfdf26da5da68dcaaf27a88e9e6735dcb9fc8d2854873be1e0a0
|
3 |
+
size 88362
|
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 sha256:85f283e1802eb6ddf4c1a49952b780c936f3ad4c16c00748af5303f58c4f1c8c
|
3 |
+
size 43762
|
ppo-LunarLander-v2/pytorch_variables.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 sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
|
3 |
+
size 864
|
ppo-LunarLander-v2/system_info.txt
CHANGED
@@ -1,7 +1,9 @@
|
|
1 |
-
OS: Linux-
|
2 |
-
Python: 3.
|
3 |
-
Stable-Baselines3:
|
4 |
-
PyTorch: 1.
|
5 |
-
GPU Enabled: True
|
6 |
-
Numpy: 1.
|
7 |
-
|
|
|
|
|
|
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: 2.1.0+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
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 251.9416903271021, "std_reward": 17.46452820688415, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-09T10:25:31.308377"}
|