initial commit

.gitattributes

@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,28 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 196.81 +/- 77.22
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+  # **PPO** Agent playing **LunarLander-v2**
+  This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+  
+  ## Usage (with Stable-baselines3)
+  TODO: Add your code
+  

config.json

@@ -0,0 +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 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 0x7f493e0753b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f493e075440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f493e0754d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f493e075560>", "_build": "<function ActorCriticPolicy._build at 0x7f493e0755f0>", "forward": "<function ActorCriticPolicy.forward at 0x7f493e075680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f493e075710>", "_predict": "<function ActorCriticPolicy._predict at 0x7f493e0757a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f493e075830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f493e0758c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f493e075950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f493e044450>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651996551.5934443, "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": 124, "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:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d1024361f8640e9ce987f730bd17612daa6fd04e29cb1bc834ad3a9e78e8e178
+size 164688

results.json

@@ -0,0 +1 @@
+{"mean_reward": 196.8076989422044, "std_reward": 77.2193956857759, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-08T09:32:11.269620"}

v61_lunar.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b46e38bc232938a805edff54975d3694f106a90da9632e9f9b9451913ac2b23e
+size 144032

v61_lunar/_stable_baselines3_version

@@ -0,0 +1 @@
+1.5.0

v61_lunar/data

@@ -0,0 +1,94 @@
+{
+    "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 0x7f493e0753b0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f493e075440>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f493e0754d0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f493e075560>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f493e0755f0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f493e075680>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f493e075710>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f493e0757a0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f493e075830>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f493e0758c0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f493e075950>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f493e044450>"
+    },
+    "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": 507904,
+    "_total_timesteps": 500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1651996551.5934443,
+    "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": 124,
+    "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
+}

v61_lunar/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:88897774db2f8d4e43063a5950f59693f5edee0dc0ec67ff7ae3a923552d2d3e
+size 84829

v61_lunar/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6cae5962f79633906ba9d1d3b0eccc5ae41645c237bb6c54b9a5d47462d7a00e
+size 43201

v61_lunar/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

v61_lunar/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.5.0
+PyTorch: 1.11.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0