First commit of lunar lander

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 258.28 +/- 21.24
+      value: 259.92 +/- 21.68
       name: mean_reward
       verified: false
 ---

config.json

@@ -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 0x7f28e65b43a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f28e65b4430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f28e65b44c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f28e65b4550>", "_build": "<function ActorCriticPolicy._build at 0x7f28e65b45e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f28e65b4670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f28e65b4700>", "_predict": "<function ActorCriticPolicy._predict at 0x7f28e65b4790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f28e65b4820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f28e65b48b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f28e65b4940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f28e65b6090>"}, "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": 1670693172144752782, "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"}}
+{"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 0x7f67fad04700>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f67fad04790>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f67fad04820>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f67fad048b0>", "_build": "<function ActorCriticPolicy._build at 0x7f67fad04940>", "forward": "<function ActorCriticPolicy.forward at 0x7f67fad049d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f67fad04a60>", "_predict": "<function ActorCriticPolicy._predict at 0x7f67fad04af0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f67fad04b80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f67fad04c10>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f67fad04ca0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f67facfe540>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1670782502867671427, "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"}}

ppo_LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fc62d32783ec04de531ea5b07a6fb9ee24147b7e33b7259a7114e3127ea68a1f
-size 147210
+oid sha256:299db289da1d7fe2600822e0031aeaeace824281d54e1f907e03544dd94f876d
+size 147214

ppo_LunarLander-v2/data

@@ -4,19 +4,19 @@
         ":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 0x7f28e65b43a0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f28e65b4430>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f28e65b44c0>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f28e65b4550>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f28e65b45e0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f28e65b4670>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f28e65b4700>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f28e65b4790>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f28e65b4820>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f28e65b48b0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f28e65b4940>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f67fad04700>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f67fad04790>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f67fad04820>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f67fad048b0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f67fad04940>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f67fad049d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f67fad04a60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f67fad04af0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f67fad04b80>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f67fad04c10>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f67fad04ca0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f28e65b6090>"
+        "_abc_impl": "<_abc_data object at 0x7f67facfe540>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -47,7 +47,7 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1670693172144752782,
+    "start_time": 1670782502867671427,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -69,7 +69,7 @@
     "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",

ppo_LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:90acaefbc980184bb882820b629da59ea7f41b17826c3a88ed567a74a3ec5a0d
+oid sha256:319aa96d08d6cfc0c6bae7b546b4786983caeec6eab77c3013cb6816480ea270
 size 87929

ppo_LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ee9ab4a7ef4ab8ca594829d7f2796601f7ba33e98790646be115b226d2d6f39e
+oid sha256:a889f3d2107c1e0506176d0fd687f9a92b1a4e0e8b51d2d65ed066c6a4589957
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 258.2778070859378, "std_reward": 21.239566594412658, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-10T17:54:31.655798"}
+{"mean_reward": 259.9175327105203, "std_reward": 21.675143119928325, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-11T18:37:01.104017"}