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: 283.41 +/- 17.24
+      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 0x7f55b33c7a70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f55b33c7b00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f55b33c7b90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f55b33c7c20>", "_build": "<function ActorCriticPolicy._build at 0x7f55b33c7cb0>", "forward": "<function ActorCriticPolicy.forward at 0x7f55b33c7d40>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f55b33c7dd0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f55b33c7e60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f55b33c7ef0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f55b33c7f80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f55b33cd050>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f55b341f2a0>"}, "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": 5013504, "_total_timesteps": 5000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651847911.7498138, "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": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 612, "n_steps": 2048, "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": "False", "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 sha256:3246a2a7693f7077aec56faddc861aecb6e8fe6fe6b2b2808c6cc37036da7310
+size 143600

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 0x7f55b33c7a70>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f55b33c7b00>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f55b33c7b90>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f55b33c7c20>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f55b33c7cb0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f55b33c7d40>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f55b33c7dd0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f55b33c7e60>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f55b33c7ef0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f55b33c7f80>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f55b33cd050>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f55b341f2a0>"
+    },
+    "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": 5013504,
+    "_total_timesteps": 5000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1651847911.7498138,
+    "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": -0.0027007999999999477,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 612,
+    "n_steps": 2048,
+    "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 sha256:2d299e91d0770e31dd65bfb924d0f977974cf4175c2a8101310e52dd3b197b83
+size 84637

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:acc9a7156308a66a0aad2902d2dbdd80e39e3b3c2b090bef6066d715650abab0
+size 43073

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: False
+Numpy: 1.21.6
+Gym: 0.21.0

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a0bbd5ed79087d53bd66bb63be2ef535e112175ddc5c6f20dc68bcd0d890396b
+size 190858

results.json

@@ -0,0 +1 @@
+{"mean_reward": 283.41093339076485, "std_reward": 17.238586729581822, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-06T15:42:52.646946"}