Course notebook 1

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: -440.34 +/- 126.76
+      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 0x7fbff48fe3a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbff48fe430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbff48fe4c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbff48fe550>", "_build": "<function ActorCriticPolicy._build at 0x7fbff48fe5e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fbff48fe670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbff48fe700>", "_predict": "<function ActorCriticPolicy._predict at 0x7fbff48fe790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbff48fe820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbff48fe8b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbff48fe940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fbff48fc1e0>"}, "verbose": 0, "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:": "gAWVgQAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZRoB5OUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=", "n": 4, "shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 131072, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670388639899760323, "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": -0.3107200000000001, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 40, "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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.17.3"}}

results.json

@@ -0,0 +1 @@
+{"mean_reward": -440.3416174243437, "std_reward": 126.76126033757052, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-07T04:53:39.705493"}

salviPPO.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f0ce3664b4ae7f6faf7142d84e74796683e177fa51c0669241c0188817b305be
+size 147006

salviPPO/_stable_baselines3_version

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

salviPPO/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 0x7fbff48fe3a0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fbff48fe430>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fbff48fe4c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fbff48fe550>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fbff48fe5e0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fbff48fe670>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fbff48fe700>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fbff48fe790>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fbff48fe820>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fbff48fe8b0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fbff48fe940>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fbff48fc1e0>"
+    },
+    "verbose": 0,
+    "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:": "gAWVgQAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZRoB5OUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=",
+        "n": 4,
+        "shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 131072,
+    "_total_timesteps": 100000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1670388639899760323,
+    "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": -0.3107200000000001,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 40,
+    "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
+}

salviPPO/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e7b62926293508b4f4ddeecd2eae00dc21df88da90066aed40c4a79420dc3e47
+size 87865

salviPPO/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a5a183ceb0aac71b5cd9645c654ed7d50ddf44d65a4ec9c2cfd936d6df26b5c2
+size 43201

salviPPO/pytorch_variables.pth

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

salviPPO/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: 3.8.15
+Stable-Baselines3: 1.6.2
+PyTorch: 1.12.1+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.17.3