{"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 0x7fcf3e3f9c60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcf3e3f9d00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcf3e3f9da0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcf3e3f9e40>", "_build": "<function ActorCriticPolicy._build at 0x7fcf3e3f9ee0>", "forward": "<function ActorCriticPolicy.forward at 0x7fcf3e3f9f80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fcf3e3fa020>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcf3e3fa0c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcf3e3fa160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcf3e3fa200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcf3e3fa2a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcf3e3fa340>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fcf3e31c4c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1740074956390688063, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAIAcqT2qSI0/e6NPPtlzx76squs8iOXUPQAAAAAAAAAAMxeUOylkKLruwaQ5q8obNlC7fztiWsS4AACAPwAAgD8A4Di64UaeuhT2rboR3dO1BMjyOgaeyDkAAIA/AACAP/OTCT4K2ZU/klv/Ph0p5b5DMBA+IA8pPgAAAAAAAAAAJnPePVJg8rni8pa7waZBOJ5KuzoIHt83AACAPwAAgD/Tkgm+0QxDP314Hjse7nG+KLqGvVX73DwAAAAAAAAAABrSLj32HES6xt5Iug9sajYGMua5wulsOQAAgD8AAIA/muwWvcOBfbpiE7Szt9sCsOoIyjgNhbgzAACAPwAAgD+m0s09exKIuuWeCDjxNAIzkCdZuo0fH7cAAAAAAACAP43l2L2k+EK77hUmPUd3/Dxl7lc8GM3VvQAAgD8AAIA/5s3LvbUFmz+WWKK+FxiLvotZJ77cNim+AAAAAAAAAADTXxw+m0KQP22Z6T5P5gO/mz0mPnptzT0AAAAAAAAAAI0mnr1JsSA9+6zdPeb24r3HU9c8ch9ovQAAAAAAAAAAjWSePQ/LTLzSS2k88N93PAQurj1XM0y9AACAPwAAgD+AlGu9KbB1upOeerkam3u04DVsutKBkjgAAIA/AACAP+ZgD72ksBK5FrBoulOpX7Y+Exs7SmKLOQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVQwwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGLvh37k4m2MAWyUTegDjAF0lEdAlXmoZuQ6qHV9lChoBkdAYeZo2XLNfWgHTegDaAhHQJV7uWUr08N1fZQoaAZHQF+os5n13+xoB03oA2gIR0CVgZfzz3AVdX2UKGgGR0BkGPrt3OfNaAdN6ANoCEdAlYMnvQWvbHV9lChoBkdAaJijLSuyNWgHTegDaAhHQJWSG3solUp1fZQoaAZHQGLVLOAy2x9oB03oA2gIR0CVm1QRwqAjdX2UKGgGR0BfHIjbBXS0aAdN6ANoCEdAlZz6Ii1RcnV9lChoBkdAZGsPbO/tY2gHTegDaAhHQJWnIkgOjIt1fZQoaAZHQGUEONPxhDxoB03oA2gIR0CVp7neizsydX2UKGgGR0BhtRP420iRaAdN6ANoCEdAlaoipR4yGnV9lChoBkdAYqBjNIK+jGgHTegDaAhHQJWrmb4Ju2t1fZQoaAZHQGYD7XHzYmNoB03oA2gIR0CVq/3Lmp2mdX2UKGgGR0BGftc4YJmeaAdL/mgIR0CVrA9mpVCHdX2UKGgGR0BjLBTKkl/paAdN6ANoCEdAlaxy+pOvdXV9lChoBkdAYi0a3I+4b2gHTegDaAhHQJW1Txx1gYx1fZQoaAZHQGdNwVKwpvxoB03oA2gIR0CVy+1+iJwbdX2UKGgGR0BkVC8SPEKmaAdN6ANoCEdAlcwQrYoRZnV9lChoBkdAXMw+UyHmBGgHTegDaAhHQJXMO0rsjVx1fZQoaAZHQEl9nA6+36RoB00BAWgIR0CVzG8ohIOIdX2UKGgGR0Bk8rJuEVWTaAdN6ANoCEdAlc5obKifx3V9lChoBkdAMzz4QBgeBGgHTRYBaAhHQJXOp2ZAprl1fZQoaAZHQGNbjwYtQKtoB03oA2gIR0CV0okLQXyidX2UKGgGR0BlEXPVurIYaAdN6ANoCEdAldOTcIqsl3V9lChoBkdAYy8J2MbWE2gHTegDaAhHQJXh6stCiRJ1fZQoaAZHQGJc/ffoA4poB03oA2gIR0CV7RJQcghbdX2UKGgGR0Bm83YpUgjhaAdN6ANoCEdAlfZmpZOi4HV9lChoBkdAZP1aTOgQH2gHTegDaAhHQJX27p0OmSB1fZQoaAZHQGKeVLJ0W/JoB03oA2gIR0CV+sLUCq6wdX2UKGgGR0BgZl3EAHVxaAdN6ANoCEdAlfrR0lqrR3V9lChoBkdAZ7Xze40/GGgHTegDaAhHQJX7MAxSHdp1fZQoaAZHQGaizHS4OMFoB03oA2gIR0CWAVhJRO1wdX2UKGgGR0Bmfm7QLNOeaAdN6ANoCEdAlhmcDW9UTHV9lChoBkdAYhqTUy57PmgHTegDaAhHQJYZu9cry2B1fZQoaAZHQGak63AmAsloB03oA2gIR0CWGeTOxB3SdX2UKGgGR0BfWBgZ0jkdaAdN6ANoCEdAlhoXE61b7nV9lChoBkdAZn0WyC4Bm2gHTegDaAhHQJYb7JzT4L11fZQoaAZHQFti4WUKRdRoB03oA2gIR0CWHCmois4ldX2UKGgGR0BhsUnPVurIaAdN6ANoCEdAliAlnmJWNnV9lChoBkdAYIUtJWeYlmgHTegDaAhHQJYhPrleWv91fZQoaAZHQE/5mjj7yhBoB00EAWgIR0CWKS/LTx5LdX2UKGgGR0Bl8Ei2UjcEaAdN6ANoCEdAli6mj4593XV9lChoBkdAZGSs189fTmgHTegDaAhHQJY40UmD15B1fZQoaAZHQGRw2ovSMLpoB03oA2gIR0CWRQpKjBVNdX2UKGgGR0BkYsHSnccmaAdN6ANoCEdAlkXmrwOOKnV9lChoBkdAXkBG/etSymgHTegDaAhHQJZJ8eJYT0x1fZQoaAZHQF+cTbnHNotoB03oA2gIR0CWSgJ2+wkgdX2UKGgGR0BlftkvsZ5zaAdN6ANoCEdAlkpju4PPLXV9lChoBkdAYkDiSaEzwmgHTegDaAhHQJZQ5W3jMmp1fZQoaAZHQGdEmTkhib5oB03oA2gIR0CWZzUAT7EYdX2UKGgGR0Bk/UF4cFQmaAdN6ANoCEdAlmdVJxvNvHV9lChoBkdAZYLlLeyiVWgHTegDaAhHQJZngZdfLLZ1fZQoaAZHQGPeElNUOutoB03oA2gIR0CWZ7QP7N0OdX2UKGgGR0BfEdShrWRSaAdN6ANoCEdAlmnKPXCj13V9lChoBkdAZThRMvh60WgHTegDaAhHQJZt+W/rSmZ1fZQoaAZHQGC3jst03fhoB03oA2gIR0CWb4mxt52RdX2UKGgGR0BlPuS0Sh8IaAdN6ANoCEdAlnodUKiPAHV9lChoBkdAZeGNqgyuZGgHTegDaAhHQJZ/tF8XvYx1fZQoaAZHQGHMOWBz3h5oB03oA2gIR0CWiduXu3MIdX2UKGgGR0Bk28aQ3gk1aAdN6ANoCEdAlpQMXWOIZnV9lChoBkdAYy+RQrMC92gHTegDaAhHQJaUoDB/I811fZQoaAZHQGH9pmmLtNVoB03oA2gIR0CWmJy1uzhQdX2UKGgGR0BlCxVU+9rXaAdN6ANoCEdAlpitnGsFMnV9lChoBkdAYfGm4RVZLmgHTegDaAhHQJaZEFB6a9d1fZQoaAZHQGcNuFYdQwdoB03oA2gIR0CWn/F8XvYwdX2UKGgGR0BieGS4e9zwaAdN6ANoCEdAlrhVGTcIq3V9lChoBkdAYIkH446wMmgHTegDaAhHQJa4d21UlzF1fZQoaAZHQGExRptaY/poB03oA2gIR0CWuKUfPompdX2UKGgGR0Bh7n9itq59aAdN6ANoCEdAlrjZSzgMt3V9lChoBkdAYm6uDBdld2gHTegDaAhHQJa65mTTvy91fZQoaAZHQFzcKhL5AQhoB03oA2gIR0CWvr0mdAgQdX2UKGgGR0BbgbvoePq+aAdN6ANoCEdAlr+2HxjJ+3V9lChoBkdAYJ+7QLNOd2gHTegDaAhHQJbG+KuSwGJ1fZQoaAZHQGTzbLMcIZ9oB03oA2gIR0CWzAmce8wpdX2UKGgGR0BgAXwmVqveaAdN6ANoCEdAltbiX2M85nV9lChoBkdAZWgAskIHDGgHTegDaAhHQJbfrbblA/t1fZQoaAZHQGh4Je3QUpNoB03oA2gIR0CW4C+bVjI8dX2UKGgGR0Bj9HVVghKUaAdN6ANoCEdAluPmDlHSW3V9lChoBkdAYbF9y925hGgHTegDaAhHQJbj9H6Mzdl1fZQoaAZHQFprZkCmuT1oB03oA2gIR0CW5EyXD3uedX2UKGgGR0Bg3R3C9AX3aAdN6ANoCEdAlupKd+Xqq3V9lChoBkdAX76J0nw5N2gHTegDaAhHQJbvA1AJLM91fZQoaAZHQGPRr433pOhoB03oA2gIR0CW7yGwiaAndX2UKGgGR0BhL9Jtix3WaAdN6ANoCEdAlu9LdvbXYnV9lChoBkdAYnbmapgkT2gHTegDaAhHQJcBRn003wV1fZQoaAZHQGKMugpSaVloB03oA2gIR0CXBA+hoM8YdX2UKGgGR0Bj9xS3solVaAdN6ANoCEdAlwj6FM7EHnV9lChoBkdAX3CHuZ1FIGgHTegDaAhHQJcKDSLIgeR1fZQoaAZHQGAMc8DB/I9oB03oA2gIR0CXEgVfNRm9dX2UKGgGR0BlD88/2TPjaAdN6ANoCEdAlxcjQ3PzF3V9lChoBkdAaReJ9iMHbGgHTegDaAhHQJcgAoG6f8N1fZQoaAZHQGD9jhUBGQVoB03oA2gIR0CXKIPznRsudX2UKGgGR0Bh31QwblzVaAdN6ANoCEdAlyj+TFERa3V9lChoBkdAYk24lQdjomgHTegDaAhHQJcsSIxgy/N1fZQoaAZHQGWN6NuLrHFoB03oA2gIR0CXLFlzEJjUdX2UKGgGR0Bnit+ocaOxaAdN6ANoCEdAlyyxT0g8sHV9lChoBkdAW/jdGiHqNmgHTegDaAhHQJcyS+HrQgN1fZQoaAZHQGXXFNDc/MZoB03oA2gIR0CXNzM0xdpqdX2UKGgGR0BhmSSeRPoFaAdN6ANoCEdAlzdV2mpEQXV9lChoBkdAZMcYlY2bX2gHTegDaAhHQJc3gACGN711fZQoaAZHQF0BgAZKnNxoB03oA2gIR0CXN7d30PH1dWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_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": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |