Upload PPO LunarLander-v2 trained agent

.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: 221.80 +/- 38.17
+      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 0x7f2d4ba35320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2d4ba353b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2d4ba35440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2d4ba354d0>", "_build": "<function ActorCriticPolicy._build at 0x7f2d4ba35560>", "forward": "<function ActorCriticPolicy.forward at 0x7f2d4ba355f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2d4ba35680>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2d4ba35710>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2d4ba357a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2d4ba35830>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2d4ba358c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2d4ba77e10>"}, "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": 1651687271.5662723, "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-5.4.188+-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-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d07e270c647c578f1c39a7c4e9c9e20a36f64d8a43790daca544f03e6f5531f4
+size 144048

ppo-LunarLander-v2/_stable_baselines3_version

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

ppo-LunarLander-v2/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 0x7f2d4ba35320>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2d4ba353b0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2d4ba35440>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2d4ba354d0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f2d4ba35560>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f2d4ba355f0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2d4ba35680>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f2d4ba35710>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2d4ba357a0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2d4ba35830>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2d4ba358c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f2d4ba77e10>"
+    },
+    "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": 1651687271.5662723,
+    "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
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f29464e4bef4f46c84fa6ea1c45eba4dff9e33909632b903ae95118bc19d3551
+size 84829

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a38c5c1607936c9f04b3d06572c773ad901bb0423fdfd8f8cd97b551e2f0392
+size 43201

ppo-LunarLander-v2/pytorch_variables.pth

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

ppo-LunarLander-v2/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 sha256:800b912ec515a6a24cc8510b32048b3712253df3b1de51adaa095ec8081e09cc
+size 255459

results.json

@@ -0,0 +1 @@
+{"mean_reward": 221.79711811688895, "std_reward": 38.16604924459104, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-04T18:50:58.632619"}