Initial commit

.gitattributes

@@ -30,3 +30,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,36 @@
+---
+library_name: stable-baselines3
+tags:
+- AntBulletEnv-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: A2C
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 1851.70 +/- 143.96
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: AntBulletEnv-v0
+      type: AntBulletEnv-v0
+---
+
+# **A2C** Agent playing **AntBulletEnv-v0**
+This is a trained model of a **A2C** agent playing **AntBulletEnv-v0**
+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
+
+...
+```

a2c-AntBulletEnv-v0.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c48e5c032596f51970802b24fcb8d2fbf908a685a8365b23ffaf84cd4fd04e9c
+size 129093

a2c-AntBulletEnv-v0/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.0

a2c-AntBulletEnv-v0/data

@@ -0,0 +1,105 @@
+{
+    "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 0x7f0c083cf370>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0c083cf400>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0c083cf490>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0c083cf520>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f0c083cf5b0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f0c083cf640>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0c083cf6d0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f0c083cf760>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0c083cf7f0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0c083cf880>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0c083cf910>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f0c083d1b40>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        ":type:": "<class 'dict'>",
+        ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
+        "log_std_init": -2,
+        "ortho_init": false,
+        "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
+        "optimizer_kwargs": {
+            "alpha": 0.99,
+            "eps": 1e-05,
+            "weight_decay": 0
+        }
+    },
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "gAWVbQIAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLHIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWcAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/lGgLSxyFlIwBQ5R0lFKUjARoaWdolGgTKJZwAAAAAAAAAAAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH+UaAtLHIWUaBZ0lFKUjA1ib3VuZGVkX2JlbG93lGgTKJYcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLHIWUaBZ0lFKUjA1ib3VuZGVkX2Fib3ZllGgTKJYcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUaCJLHIWUaBZ0lFKUjApfbnBfcmFuZG9tlE51Yi4=",
+        "dtype": "float32",
+        "_shape": [
+            28
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
+        "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]",
+        "high": "[1. 1. 1. 1. 1. 1. 1. 1.]",
+        "bounded_below": "[ True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True]",
+        "_np_random": null
+    },
+    "n_envs": 4,
+    "num_timesteps": 2000000,
+    "_total_timesteps": 2000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1664121269.9495723,
+    "learning_rate": 0.00096,
+    "tensorboard_log": "./tensorboard",
+    "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:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_episode_num": 0,
+    "use_sde": true,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": 0.0,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 62500,
+    "n_steps": 8,
+    "gamma": 0.99,
+    "gae_lambda": 0.9,
+    "ent_coef": 0.0,
+    "vf_coef": 0.4,
+    "max_grad_norm": 0.5,
+    "normalize_advantage": false
+}

a2c-AntBulletEnv-v0/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ac1cc184572a77592f10a7688c5f520f1afe68471d6dbb509f285c6797419afd
+size 56126

a2c-AntBulletEnv-v0/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d5d1f9b4d7225c607bacc1f17ab97d39508be970f235ce2418cfb3332cfbde0a
+size 56766

a2c-AntBulletEnv-v0/pytorch_variables.pth

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

a2c-AntBulletEnv-v0/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.15.0-47-generic-x86_64-with-glibc2.35 #51-Ubuntu SMP Thu Aug 11 07:51:15 UTC 2022
+Python: 3.10.4
+Stable-Baselines3: 1.6.0
+PyTorch: 1.12.1+cu116
+GPU Enabled: True
+Numpy: 1.23.3
+Gym: 0.21.0

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 0x7f0c083cf370>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0c083cf400>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0c083cf490>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0c083cf520>", "_build": "<function ActorCriticPolicy._build at 0x7f0c083cf5b0>", "forward": "<function ActorCriticPolicy.forward at 0x7f0c083cf640>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0c083cf6d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0c083cf760>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0c083cf7f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0c083cf880>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0c083cf910>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f0c083d1b40>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [28], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_np_random": null}, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1664121269.9495723, "learning_rate": 0.00096, "tensorboard_log": "./tensorboard", "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:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 62500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.15.0-47-generic-x86_64-with-glibc2.35 #51-Ubuntu SMP Thu Aug 11 07:51:15 UTC 2022", "Python": "3.10.4", "Stable-Baselines3": "1.6.0", "PyTorch": "1.12.1+cu116", "GPU Enabled": "True", "Numpy": "1.23.3", "Gym": "0.21.0"}}

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dae4f7814da5dca721c98edb549c186b95e45d349851d08b97bcce7caa82c8c4
+size 1098722

results.json

@@ -0,0 +1 @@
+{"mean_reward": 1851.6974431856768, "std_reward": 143.957096249045, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-09-26T07:26:29.423345"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c6d0a47708d4027f69aa8322cc7904e8eb0a29209a8be007ab4a1e10676c93b1
+size 2521