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: 1057.92 +/- 271.25
+      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:cb74acb9a2c60f7090f0cc171b36ffd70e4c3df681fbec8a0962a621eb29837f
+size 129528

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 0x7f8d452ccf70>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8d452cd000>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8d452cd090>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8d452cd120>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f8d452cd1b0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f8d452cd240>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8d452cd2d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8d452cd360>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f8d452cd3f0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8d452cd480>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8d452cd510>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8d452cd5a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f8d452c6880>"
+    },
+    "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": 1500000,
+    "_total_timesteps": 1500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1687682361952536692,
+    "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:": "gAWVQwwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQH9p2qT8pCuMAWyUTegDjAF0lEdAo01FdcB2fXV9lChoBkdAk1ruQlruY2gHTegDaAhHQKNPFNcGC7N1fZQoaAZHQJVEohmoR7JoB03oA2gIR0CjTzE2gnMMdX2UKGgGR0CRIw8scyWSaAdN6ANoCEdAo1UDnNgSe3V9lChoBkdAhnLAg5imVWgHTegDaAhHQKNcfuLJjlR1fZQoaAZHQJRnOXiR4hVoB03oA2gIR0CjXwLRSgoPdX2UKGgGR0CSF6dKdxyXaAdN6ANoCEdAo18e9Jz1b3V9lChoBkdAlCEE078vVWgHTegDaAhHQKNkfttygf51fZQoaAZHQHyqItYjjaRoB03oA2gIR0CjaWH7xd6cdX2UKGgGR0CGb3og3cYZaAdN6ANoCEdAo2szPIGQjnV9lChoBkdAj2Ygk9lmOGgHTegDaAhHQKNrUPaL4vh1fZQoaAZHQIzTJSvTw2FoB03oA2gIR0CjcMgydnTRdX2UKGgGR0CRu3aSs8xLaAdN6ANoCEdAo3cxUcXFcnV9lChoBkdAjs14XoC+12gHTegDaAhHQKN6CWepXIV1fZQoaAZHQIr9/+MqBmRoB03oA2gIR0CjejUCih38dX2UKGgGR0CMr1wXIlt1aAdN6ANoCEdAo4CoGSpzcXV9lChoBkdAkFcswUQCjmgHTegDaAhHQKOFmdbPhQ51fZQoaAZHQH/UK4x1xKhoB03oA2gIR0Cjh2RusLfDdX2UKGgGR0CBiFu7YkE+aAdN6ANoCEdAo4d/6O5rg3V9lChoBkdAiHxFAu7HyWgHTegDaAhHQKOM0OoYNy51fZQoaAZHQJI/Hp9qk/NoB03oA2gIR0CjkeINutOmdX2UKGgGR0B7Lf5FgDzRaAdN6ANoCEdAo5R+DDjzZ3V9lChoBkdAkjasDSw4bWgHTegDaAhHQKOUpKtga3t1fZQoaAZHQI5ifmJWNm1oB03oA2gIR0CjnJDNhVlxdX2UKGgGR0CRL5T6SDAaaAdN6ANoCEdAo6GgvcrRSnV9lChoBkdAhqIaxxDLKWgHTegDaAhHQKOjdS3LFGZ1fZQoaAZHQIt3HOfNA1NoB03oA2gIR0Cjo5Cay8jBdX2UKGgGR0CScEeumrKeaAdN6ANoCEdAo6j27g88tHV9lChoBkdAd72f3evZAmgHTegDaAhHQKOt7zqbBoF1fZQoaAZHQI2k4uyu6mRoB03oA2gIR0Cjr7eyZ8a5dX2UKGgGR0B8OHgTAWSEaAdN6ANoCEdAo6/UtPHktHV9lChoBkdAji6e0PYnOWgHTegDaAhHQKO3ppmEoOR1fZQoaAZHQIx4n+0gKWtoB03oA2gIR0CjvbzundftdX2UKGgGR0CQLGYsNDtxaAdN6ANoCEdAo7+VM23rlnV9lChoBkdAkZhx9gF5fWgHTegDaAhHQKO/sLCN0eV1fZQoaAZHQJSTVT4tYjloB03oA2gIR0CjxSTSb6P9dX2UKGgGR0CE6fUMG5c1aAdN6ANoCEdAo8oTZamoBXV9lChoBkdAjoHbItDlYGgHTegDaAhHQKPL6R2bG3p1fZQoaAZHQJSBnOgQHzJoB03oA2gIR0CjzAadc0LudX2UKGgGR0CUTKc5sCT2aAdN6ANoCEdAo9Kgd8zAOHV9lChoBkdAkEJ5BC2MKmgHTegDaAhHQKPaBaA4GUx1fZQoaAZHQJJVPNPgvUVoB03oA2gIR0Cj2+tZ3cHodX2UKGgGR0CSZYsXSBsiaAdN6ANoCEdAo9wI33pOe3V9lChoBkdAioHhikO7QWgHTegDaAhHQKPhXpSJj2B1fZQoaAZHQHTA1ktmL+BoB037AmgIR0Cj42dP1tfpdX2UKGgGR0CDSZ9vS+g2aAdN6ANoCEdAo+g5Qk5ZKXV9lChoBkdAglQKg7HQyGgHTegDaAhHQKPoVlPrOZ91fZQoaAZHQIeaAAXEZR9oB03oA2gIR0Cj7bvxQSBcdX2UKGgGR0CCY4mZ3LV4aAdN6ANoCEdAo/Cp3PiT+3V9lChoBkdAgsB+FUQ042gHTegDaAhHQKP4BaHKwIN1fZQoaAZHQH9sVGb1AZ9oB03oA2gIR0Cj+DJsXSBtdX2UKGgGR0CP5NmA9V3maAdN6ANoCEdAo/3UwWWQfnV9lChoBkdAj/128Zk08GgHTegDaAhHQKP/6AYHgP51fZQoaAZHQIlFClJpWWBoB03oA2gIR0CkBJ8D0UXYdX2UKGgGR0B5yEtpVS4waAdN6ANoCEdApAS7LbHp8nV9lChoBkdAZS/bTtsvZmgHS5ZoCEdApAaI7Rv3rXV9lChoBkdAk1kMo6S1V2gHTegDaAhHQKQKCnk1dgR1fZQoaAZHQIWAoQL/jsFoB03oA2gIR0CkDBOvMbFTdX2UKGgGR0CQuMroW56MaAdN6ANoCEdApBKrHhjvu3V9lChoBkdAjzfi6xxDLWgHTegDaAhHQKQVqWv8qF11fZQoaAZHQIrAaJVKf4BoB03oA2gIR0CkGep+MIeHdX2UKGgGR0CLlpLFn7HiaAdN6ANoCEdApBv1AzHjqHV9lChoBkdAlDjmSEDhcmgHTegDaAhHQKQgsiAUcn51fZQoaAZHQIfuCvq1PWRoB03oA2gIR0CkIq6PsAvMdX2UKGgGR0CMGdvWpZOjaAdN6ANoCEdApCY3MQmNR3V9lChoBkdAjJ5H8jzI3mgHTegDaAhHQKQoPdGiHqN1fZQoaAZHQJNXa8tf5UNoB03oA2gIR0CkLba7VawEdX2UKGgGR0CSHfXTmW+oaAdN6ANoCEdApDCE45tFa3V9lChoBkdAkCDAWepXIWgHTegDaAhHQKQ19SrHU+d1fZQoaAZHQJMC0JOWSlpoB03oA2gIR0CkOAplJ6IFdX2UKGgGR0CTUk/z8P4EaAdN6ANoCEdApDzBw++ueXV9lChoBkdAjLwEBbOeKGgHTegDaAhHQKQ+s5d4Vyp1fZQoaAZHQJBr5+c6Nl1oB03oA2gIR0CkQjfzreImdX2UKGgGR0CO5RPGhmGuaAdN6ANoCEdApERIsNDtxHV9lChoBkdAhi3bXpW3jWgHTegDaAhHQKRJIrVe8f51fZQoaAZHQJJBf+bVjI9oB03oA2gIR0CkS455JK8MdX2UKGgGR0CDbR0PH1e0aAdN6ANoCEdApFDGplz2e3V9lChoBkdAkGi123azvGgHTegDaAhHQKRT68zQ/ot1fZQoaAZHQJH3BOzposZoB03oA2gIR0CkWSkoF3Y+dX2UKGgGR0CT4KQRPGhmaAdN6ANoCEdApFsS0Sh8IHV9lChoBkdAgVB3EyckMWgHTegDaAhHQKRehzI3irF1fZQoaAZHQIWM07QswtdoB03oA2gIR0CkYH7bcoH+dX2UKGgGR0CHtUYht+CsaAdN6ANoCEdApGVCTOgQH3V9lChoBkdAjwknZkCmuWgHTegDaAhHQKRnMejEehh1fZQoaAZHQIt4kWAPNFBoB03oA2gIR0Cka3tyo4uLdX2UKGgGR0CQvovfj0cwaAdN6ANoCEdApG599x6v7nV9lChoBkdAh5Oz/Q0GeWgHTegDaAhHQKR1M2xY7q91fZQoaAZHQInd2WMS9M9oB03oA2gIR0CkdyJV0cOtdX2UKGgGR0CQUZv+fh/BaAdN6ANoCEdApHqulKsdUHV9lChoBkdAiGF+N96Tn2gHTegDaAhHQKR8sxSHdoF1fZQoaAZHQJTxxvm5lOJoB03oA2gIR0CkgW9f9gnddX2UKGgGR0CBi4fMfRu1aAdN6ANoCEdApINiBNEgGXV9lChoBkdAiSwmTTvy9WgHTegDaAhHQKSG0CU5dW11fZQoaAZHQJFjiHTI/7loB03oA2gIR0CkiS+J53TvdX2UKGgGR0CVwed9Dx9YaAdN6ANoCEdApJBJ/5LytnV9lChoBkdAlK5ysny/bmgHTegDaAhHQKSTUHIIWxh1fZQoaAZHQJP8IwEhaDBoB03oA2gIR0Cklu7oKUmldX2UKGgGR0B56gMXrMTwaAdN6ANoCEdApJj+ATZg5XV9lChoBkdAhVeHEl3QlmgHTegDaAhHQKSd0V2Rq491fZQoaAZHQImCjVrhzeZoB03oA2gIR0Ckn85TAFgVdWUu"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 46875,
+    "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,
+    "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuDQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz9PdRBNVR1phZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    }
+}

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

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:069ddc342e82eac0403aad674f261a209684f19d315eb0ab84ca0e3f0940b833
+size 56190

a2c-AntBulletEnv-v0/policy.pth ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:1e9108cc099f48b8743c6fe9b15dc314b76b9315e62ebd6fdf1e03ab2ec959c7
+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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 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 0x7f8d452ccf70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8d452cd000>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8d452cd090>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8d452cd120>", "_build": "<function ActorCriticPolicy._build at 0x7f8d452cd1b0>", "forward": "<function ActorCriticPolicy.forward at 0x7f8d452cd240>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8d452cd2d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8d452cd360>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8d452cd3f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8d452cd480>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8d452cd510>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8d452cd5a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f8d452c6880>"}, "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": 1500000, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1687682361952536692, "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": 46875, "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, "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 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": 1057.9228882504626, "std_reward": 271.24593961956543, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-25T09:38:42.607471"}

vec_normalize.pkl ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:7189840e68a66dd5db582ef47274faa7d41373344edc3b7ef73834f055893a09
+size 2376