First commit of lunar lander

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 258.28 +/- 21.24
+      name: mean_reward
+      verified: false
+---
+
+# **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
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

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 0x7f28e65b43a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f28e65b4430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f28e65b44c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f28e65b4550>", "_build": "<function ActorCriticPolicy._build at 0x7f28e65b45e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f28e65b4670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f28e65b4700>", "_predict": "<function ActorCriticPolicy._predict at 0x7f28e65b4790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f28e65b4820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f28e65b48b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f28e65b4940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f28e65b6090>"}, "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": 1670693172144752782, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "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:fc62d32783ec04de531ea5b07a6fb9ee24147b7e33b7259a7114e3127ea68a1f
+size 147210

ppo_LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

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 0x7f28e65b43a0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f28e65b4430>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f28e65b44c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f28e65b4550>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f28e65b45e0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f28e65b4670>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f28e65b4700>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f28e65b4790>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f28e65b4820>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f28e65b48b0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f28e65b4940>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f28e65b6090>"
+    },
+    "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": 1670693172144752782,
+    "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 sha256:90acaefbc980184bb882820b629da59ea7f41b17826c3a88ed567a74a3ec5a0d
+size 87929

ppo_LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ee9ab4a7ef4ab8ca594829d7f2796601f7ba33e98790646be115b226d2d6f39e
+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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.8.16
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu116
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 258.2778070859378, "std_reward": 21.239566594412658, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-10T17:54:31.655798"}