First 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: 256.88 +/- 20.14
+      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 0x7fa54a8fe440>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa54a8fe4d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa54a8fe560>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa54a8fe5f0>", "_build": "<function ActorCriticPolicy._build at 0x7fa54a8fe680>", "forward": "<function ActorCriticPolicy.forward at 0x7fa54a8fe710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa54a8fe7a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fa54a8fe830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa54a8fe8c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa54a8fe950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa54a8fe9e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fa54a93bd50>"}, "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": 1651685103.9435441, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJrtOb2ugZW6pYu0uh/9Ezr6lEE5BoUBOwAAgD8AAIA/RtlzPs3fkD8m+Xk+P3P3vofwgz5aDEC7AAAAAAAAAABN7Ti9q266P/tO3b6cgqk9xoI1vAVLwr0AAAAAAAAAADOWST4oJrq8KM1cu8n6zjkn9iS+ioqWOgAAgD8AAIA/02sEvi5wlry+Z+A81X4NvqP/xjzToee9AACAPwAAgD/6V1w+KUZ+P84BwT5li+q+nGq9Pm40KT0AAAAAAAAAAA1k0737YNU90np5vX0RnL7xvBu9RcwPPAAAAAAAAAAAWposvhz3Qrx1FE+9Jr2du3ozqj0ZeIE8AACAPwAAgD/ayDw+bdaZPuhhLb4NFa2+cRk7PNCuQ70AAAAAAAAAAAa/Qz5o0668xrIAPFyZgbpNfiC+TPBKuwAAgD8AAIA/YFU2vt9BljxzdUU+EyIQvkYLBr7cpyG/AAAAAAAAAABgRBO+rj+wuq7l0bvJFwe8dtVpPPbJ474AAAAAAACAP03HHb3svss8GaSpPUmGDr7wpKU9/rA7vQAAAAAAAAAA/TJvvgGQ3bxWVom7fZ/tub45Sj4qJLA6AACAPwAAgD/GYkw+P2MGPzJ+7jtG4aC+iDD8PTp2m70AAAAAAAAAAGY4sz2F7Iw8N5whvgICtL0BLkQ5wIn9vAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": 310, "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-5.4.188+-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"}}

ppo-LunarLander-v3.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b8be9d2e3183314d7d616d7f23bfe310e07246a0f82f3228ae73aceb28e2ab13
+size 144025

ppo-LunarLander-v3/_stable_baselines3_version

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

ppo-LunarLander-v3/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 0x7fa54a8fe440>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa54a8fe4d0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa54a8fe560>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa54a8fe5f0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fa54a8fe680>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fa54a8fe710>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa54a8fe7a0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fa54a8fe830>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa54a8fe8c0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa54a8fe950>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa54a8fe9e0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fa54a93bd50>"
+    },
+    "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": 1651685103.9435441,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    },
+    "_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": 310,
+    "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
+}

ppo-LunarLander-v3/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1e1f20753d05d9c9a2306a0fcc1136ed6dfcc0fc2613dc738741a40415b1710f
+size 84893

ppo-LunarLander-v3/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:633bc8bb77cc1056f45721aa4777b62d3b6c8743a3a273d4739d4ce62fc99b38
+size 43201

ppo-LunarLander-v3/pytorch_variables.pth

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

ppo-LunarLander-v3/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

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:400264d2ee63c8b853e73960503ebfd32a9e921e439a407e43f5ada4f61d3f34
+size 193352

results.json

@@ -0,0 +1 @@
+{"mean_reward": 256.87544511837757, "std_reward": 20.143066122892833, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-04T17:47:46.097626"}