Initial commit

Browse files

Files changed (11) hide show

README.md +37 -0
a2c-AntBulletEnv-v0.zip +3 -0
a2c-AntBulletEnv-v0/_stable_baselines3_version +1 -0
a2c-AntBulletEnv-v0/data +111 -0
a2c-AntBulletEnv-v0/policy.optimizer.pth +3 -0
a2c-AntBulletEnv-v0/policy.pth +3 -0
a2c-AntBulletEnv-v0/pytorch_variables.pth +3 -0
a2c-AntBulletEnv-v0/system_info.txt +9 -0
config.json +1 -0
results.json +1 -0
vec_normalize.pkl +3 -0

README.md ADDED Viewed

	@@ -0,0 +1,37 @@

+---
+library_name: stable-baselines3
+tags:
+- AntBulletEnv-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: A2C
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: AntBulletEnv-v0
+      type: AntBulletEnv-v0
+    metrics:
+    - type: mean_reward
+      value: 1080.97 +/- 252.97
+      name: mean_reward
+      verified: false
+---
+# **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 ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:27ea6a9d937e401488fcd8003256916822a9220503330527d075468c35aa9606
+size 129529

a2c-AntBulletEnv-v0/_stable_baselines3_version ADDED Viewed

	@@ -0,0 +1 @@


1	+ 2.0.0

a2c-AntBulletEnv-v0/data ADDED Viewed

	@@ -0,0 +1,111 @@

+{
+    "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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7d4fc3957400>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d4fc3957490>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d4fc3957520>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d4fc39575b0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7d4fc3957640>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7d4fc39576d0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d4fc3957760>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d4fc39577f0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7d4fc3957880>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d4fc3957910>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d4fc39579a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d4fc3957a30>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7d4fc3959600>"
+    },
+    "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
+        }
+    },
+    "num_timesteps": 2000000,
+    "_total_timesteps": 2000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1689225995998748512,
+    "learning_rate": 0.00096,
+    "tensorboard_log": null,
+    "_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,
+    "_stats_window_size": 100,
+    "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,
+    "vf_coef": 0.4,
+    "max_grad_norm": 0.5,
+    "normalize_advantage": false,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "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]",
+        "_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]",
+        "low_repr": "-inf",
+        "high_repr": "inf",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True]",
+        "_shape": [
+            8
+        ],
+        "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]",
+        "high": "[1. 1. 1. 1. 1. 1. 1. 1.]",
+        "low_repr": "-1.0",
+        "high_repr": "1.0",
+        "_np_random": null
+    },
+    "n_envs": 4,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    }
+}

a2c-AntBulletEnv-v0/policy.optimizer.pth ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:dfac646b027a0003101f7c7c2aa1d8fec33a12976315715d2386277df64ee555
+size 56190

a2c-AntBulletEnv-v0/policy.pth ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:fdca40d6c12911c1c4acaf26d131531231c76c0c82fd9ce95364a2f671ccba86
+size 56894

a2c-AntBulletEnv-v0/pytorch_variables.pth ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

a2c-AntBulletEnv-v0/system_info.txt ADDED Viewed

	@@ -0,0 +1,9 @@

+- OS: Linux-5.15.109+-x86_64-with-glibc2.31 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0
+- PyTorch: 2.0.1+cu118
+- GPU Enabled: True
+- Numpy: 1.22.4
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

config.json ADDED Viewed

	@@ -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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7d4fc3957400>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d4fc3957490>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d4fc3957520>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d4fc39575b0>", "_build": "<function ActorCriticPolicy._build at 0x7d4fc3957640>", "forward": "<function ActorCriticPolicy.forward at 0x7d4fc39576d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d4fc3957760>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d4fc39577f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7d4fc3957880>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d4fc3957910>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d4fc39579a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d4fc3957a30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d4fc3959600>"}, "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}}, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1689225995998748512, "learning_rate": 0.00096, "tensorboard_log": null, "_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, "_stats_window_size": 100, "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, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "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]", "_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]", "low_repr": "-inf", "high_repr": "inf", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.31 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

results.json ADDED Viewed

	@@ -0,0 +1 @@


1	+ {"mean_reward": 1080.9737053739896, "std_reward": 252.96634191380815, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-13T06:43:36.456447"}

vec_normalize.pkl ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:22a6c931b7b864bd596070337f83accc7fbda4bd77d96fdc2c34324b3b570fd5
+size 2376