Upload PPO LunarLander-v2-3 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: 294.85 +/- 15.48
+      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 0x7fd9de375830>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd9de3758c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd9de375950>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd9de3759e0>", "_build": "<function ActorCriticPolicy._build at 0x7fd9de375a70>", "forward": "<function ActorCriticPolicy.forward at 0x7fd9de375b00>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd9de375b90>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd9de375c20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd9de375cb0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd9de375d40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd9de375dd0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fd9de3c38a0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "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, "_shape": [8]}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFZHR5cGWUjAVudW1weZSMBWR0eXBllJOUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE6MBl9zaGFwZZQpdWIu", "n": 4, "dtype": "int64", "_np_random": null, "_shape": []}, "n_envs": 16, "num_timesteps": 10010624, "_total_timesteps": 10000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651950185.1758037, "learning_rate": 0.001, "tensorboard_log": "./logs/", "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": -0.0010623999999999079, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 7332, "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:": "gAWVoQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxzQzpcVXNlcnNcZGFuaWVcQW5hY29uZGEzXGVudnNcc3RhYmxlYmFzZWxpbmVzLXB5MzczLWh1Z2dpbmdmYWNlXGxpYlxzaXRlLXBhY2thZ2VzXHN0YWJsZV9iYXNlbGluZXMzXGNvbW1vblx1dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5RoDXVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+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"}}

ppo-LunarLander-v2-3.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2359f2b362e4a076d29793dba339d996834db08b0258954dd94d6ce599de9276
+size 143958

ppo-LunarLander-v2-3/_stable_baselines3_version

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

ppo-LunarLander-v2-3/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 0x7fd9de375830>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd9de3758c0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd9de375950>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd9de3759e0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fd9de375a70>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fd9de375b00>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd9de375b90>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fd9de375c20>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd9de375cb0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd9de375d40>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd9de375dd0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fd9de3c38a0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "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,
+        "_shape": [
+            8
+        ]
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFZHR5cGWUjAVudW1weZSMBWR0eXBllJOUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE6MBl9zaGFwZZQpdWIu",
+        "n": 4,
+        "dtype": "int64",
+        "_np_random": null,
+        "_shape": []
+    },
+    "n_envs": 16,
+    "num_timesteps": 10010624,
+    "_total_timesteps": 10000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1651950185.1758037,
+    "learning_rate": 0.001,
+    "tensorboard_log": "./logs/",
+    "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": -0.0010623999999999079,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 7332,
+    "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-v2-3/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c0187f0c48024c693843efcd664772af2f486779babb3108984104ca759c8e44
+size 84893

ppo-LunarLander-v2-3/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0f90a996802d6fbc47daf027ca1e1ea12ba74bc12d457732a5b9ef6306c48968
+size 43201

ppo-LunarLander-v2-3/pytorch_variables.pth

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

ppo-LunarLander-v2-3/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 sha256:6be3281b7459d49e6a0cf9aa0ac192a69ecaea0059c47235ba2772256d8edd2d
+size 196808

results.json

@@ -0,0 +1 @@
+{"mean_reward": 294.8515792546888, "std_reward": 15.477751870871975, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-10T01:25:46.450757"}