Second 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 +47 -45
- 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 +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: 166.43 +/- 108.68
|
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 0x7f10b2f6c160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f10b2f6c1f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f10b2f6c280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f10b2f6c310>", "_build": "<function ActorCriticPolicy._build at 0x7f10b2f6c3a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f10b2f6c430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f10b2f6c4c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f10b2f6c550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f10b2f6c5e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f10b2f6c670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f10b2f6c700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f10b2f67600>"}, "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": 16384, "_total_timesteps": 1000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670325020652675323, "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": -15.384, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 8, "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": "3.8.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+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 0x7efb6818daf0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efb6818db80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efb6818dc10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efb6818dca0>", "_build": "<function ActorCriticPolicy._build at 0x7efb6818dd30>", "forward": "<function ActorCriticPolicy.forward at 0x7efb6818ddc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7efb6818de50>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efb6818dee0>", "_predict": "<function ActorCriticPolicy._predict at 0x7efb6818df70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efb68192040>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efb681920d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efb68192160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7efb68190c00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681370545004590027, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAKaQPT5lV6Q/qqg+PlXRBb4hVQo+qAPePAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3912, "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": 1, "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-5.10.147+-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"}}
|
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:bf6a22e12b4d900544a212274dabfb478f1ed228bbe6c31bb9d53c349b780754
|
3 |
+
size 146737
|
ppo-LunarLander-v2/_stable_baselines3_version
CHANGED
@@ -1 +1 @@
|
|
1 |
-
1.
|
|
|
1 |
+
1.8.0
|
ppo-LunarLander-v2/data
CHANGED
@@ -3,79 +3,81 @@
|
|
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 |
-
"
|
24 |
-
|
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": 16384,
|
46 |
-
"_total_timesteps": 1000,
|
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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+
|
56 |
},
|
57 |
"_last_obs": {
|
58 |
":type:": "<class 'numpy.ndarray'>",
|
59 |
-
":serialized:": "
|
60 |
},
|
61 |
"_last_episode_starts": {
|
62 |
":type:": "<class 'numpy.ndarray'>",
|
63 |
-
":serialized:": "
|
64 |
},
|
65 |
"_last_original_obs": null,
|
66 |
"_episode_num": 0,
|
67 |
"use_sde": false,
|
68 |
"sde_sample_freq": -1,
|
69 |
-
"_current_progress_remaining": -
|
|
|
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": 0.999,
|
81 |
"gae_lambda": 0.98,
|
@@ -86,7 +88,7 @@
|
|
86 |
"n_epochs": 4,
|
87 |
"clip_range": {
|
88 |
":type:": "<class 'function'>",
|
89 |
-
":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+
|
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 0x7efb6818daf0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efb6818db80>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efb6818dc10>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efb6818dca0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7efb6818dd30>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7efb6818ddc0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7efb6818de50>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efb6818dee0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7efb6818df70>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efb68192040>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efb681920d0>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7efb68192160>",
|
19 |
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7efb68190c00>"
|
21 |
},
|
22 |
"verbose": 1,
|
23 |
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1000448,
|
25 |
+
"_total_timesteps": 1000000,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
26 |
"_num_timesteps_at_start": 0,
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
+
"start_time": 1681370545004590027,
|
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:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAKaQPT5lV6Q/qqg+PlXRBb4hVQo+qAPePAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
|
39 |
},
|
40 |
"_last_episode_starts": {
|
41 |
":type:": "<class 'numpy.ndarray'>",
|
42 |
+
":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
|
43 |
},
|
44 |
"_last_original_obs": null,
|
45 |
"_episode_num": 0,
|
46 |
"use_sde": false,
|
47 |
"sde_sample_freq": -1,
|
48 |
+
"_current_progress_remaining": -0.00044800000000000395,
|
49 |
+
"_stats_window_size": 100,
|
50 |
"ep_info_buffer": {
|
51 |
":type:": "<class 'collections.deque'>",
|
52 |
+
":serialized:": "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"
|
53 |
},
|
54 |
"ep_success_buffer": {
|
55 |
":type:": "<class 'collections.deque'>",
|
56 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
57 |
},
|
58 |
+
"_n_updates": 3912,
|
59 |
+
"observation_space": {
|
60 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
61 |
+
":serialized:": "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",
|
62 |
+
"dtype": "float32",
|
63 |
+
"_shape": [
|
64 |
+
8
|
65 |
+
],
|
66 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
67 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
68 |
+
"bounded_below": "[False False False False False False False False]",
|
69 |
+
"bounded_above": "[False False False False False False False False]",
|
70 |
+
"_np_random": null
|
71 |
+
},
|
72 |
+
"action_space": {
|
73 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
74 |
+
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
|
75 |
+
"n": 4,
|
76 |
+
"_shape": [],
|
77 |
+
"dtype": "int64",
|
78 |
+
"_np_random": null
|
79 |
+
},
|
80 |
+
"n_envs": 1,
|
81 |
"n_steps": 1024,
|
82 |
"gamma": 0.999,
|
83 |
"gae_lambda": 0.98,
|
|
|
88 |
"n_epochs": 4,
|
89 |
"clip_range": {
|
90 |
":type:": "<class 'function'>",
|
91 |
+
":serialized:": "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"
|
92 |
},
|
93 |
"clip_range_vf": null,
|
94 |
"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:d293ede03980fb447ff0921b9faee794e0cb5be079803bfdf1453ad30e160b71
|
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:bf6fb8163ef02349f6678464ea4175ebf684bb5b96aaa92e5d91f5e13c99795e
|
3 |
+
size 43329
|
ppo-LunarLander-v2/system_info.txt
CHANGED
@@ -1,7 +1,7 @@
|
|
1 |
-
OS: Linux-5.10.
|
2 |
-
Python: 3.
|
3 |
-
Stable-Baselines3: 1.
|
4 |
-
PyTorch:
|
5 |
-
GPU Enabled: True
|
6 |
-
Numpy: 1.
|
7 |
-
Gym: 0.21.0
|
|
|
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: 1.8.0
|
4 |
+
- PyTorch: 2.0.0+cu118
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.22.4
|
7 |
+
- Gym: 0.21.0
|
replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 166.42562620038012, "std_reward": 108.6843495351044, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-13T08:12:36.423709"}
|