{"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 0x7dcb61f7db40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7dcb61f7dbd0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7dcb61f7dc60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7dcb61f7dcf0>", "_build": "<function ActorCriticPolicy._build at 0x7dcb61f7dd80>", "forward": "<function ActorCriticPolicy.forward at 0x7dcb61f7de10>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7dcb61f7dea0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7dcb61f7df30>", "_predict": "<function ActorCriticPolicy._predict at 0x7dcb61f7dfc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7dcb61f7e050>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7dcb61f7e0e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7dcb61f7e170>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7dcb61f88400>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1700892148760920063, "learning_rate": 0.0003, "tensorboard_log": null, "_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": -0.015808000000000044, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVQgwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGGP4p2ECeWMAWyUTegDjAF0lEdAk8szR6Ww/3V9lChoBkdAXf/Go73fymgHTegDaAhHQJPRS1a4c3l1fZQoaAZHQGGhnoX9BKNoB03oA2gIR0CT0mYI0IkadX2UKGgGR0Bg0falDWsjaAdN6ANoCEdAk9LgymALA3V9lChoBkdAYoHkXk5p8GgHTegDaAhHQJPUcwpON5t1fZQoaAZHQGMgcTakAPxoB03oA2gIR0CT4G2HLzPKdX2UKGgGR0Bg07rqt5lfaAdN6ANoCEdAk+Y6oIfKZHV9lChoBkdAWqHq/ub7TGgHTegDaAhHQJPny704BFN1fZQoaAZHQF89TRIBikRoB03oA2gIR0CT8DfhuO0cdX2UKGgGR0BfqrnX/YJ3aAdN6ANoCEdAk/V/YjB2wHV9lChoBkdAYtd6LOzIFWgHTegDaAhHQJQDx5Pdl/Z1fZQoaAZHQFz2AymALApoB03oA2gIR0CUBC0ZFXq8dX2UKGgGR0BdcTtw71ZlaAdN6ANoCEdAlAtWhM8HOnV9lChoBkdAYYzPAO8TSWgHTegDaAhHQJQSr3lCCz11fZQoaAZHQDI4nlXA/LVoB0voaAhHQJQovrxAjY91fZQoaAZHQGUYwWepXIVoB03oA2gIR0CUKzNwR5C4dX2UKGgGR0BhdyEYfnwHaAdN6ANoCEdAlC24ysS00HV9lChoBkdAXm/6qKgqVmgHTegDaAhHQJQuDuhK15V1fZQoaAZHQF5zTDO1OTJoB03oA2gIR0CUNq+so2GZdX2UKGgGR0Bb8oT4+KTCaAdN6ANoCEdAlDhVrqMWGnV9lChoBkdAZTe1vVEux2gHTegDaAhHQJQ49p48lol1fZQoaAZHQGIGIF3Y+StoB03oA2gIR0CUOyOS4e90dX2UKGgGR0BYYlPznRsuaAdN6ANoCEdAlEQDohY/3XV9lChoBkdAYTJ7AtWdVmgHTegDaAhHQJRHwq+ajN91fZQoaAZHQF6yegte2NNoB03oA2gIR0CUSL7GvOhTdX2UKGgGR8A3OUBGQSzxaAdNDQFoCEdAlErT3AVO9HV9lChoBkdAXAd5nlGPP2gHTegDaAhHQJRN2QzUI9l1fZQoaAZHQGNPkGiYb85oB03oA2gIR0CUUS7b+Lm7dX2UKGgGR0AnIiAUcn3MaAdL52gIR0CUVgVp9JBgdX2UKGgGR0BjhHUe+23KaAdN6ANoCEdAlF2dZRsMzHV9lChoBkdAYdL9cbBGhGgHTegDaAhHQJRkbgNwzch1fZQoaAZHQGOR7Lt/nW9oB03oA2gIR0CUbeJbt7a7dX2UKGgGR0BfoKWcBltkaAdN6ANoCEdAlHJLXDm8unV9lChoBkdAYCLvjOs1bmgHTegDaAhHQJSLkz2vjfh1fZQoaAZHQGCLkxqO939oB03oA2gIR0CUjY+HaewtdX2UKGgGR0BcZO8f3evZaAdN6ANoCEdAlI3b+DOC5HV9lChoBkdAYhv06o2n9GgHTegDaAhHQJSVhS1maph1fZQoaAZHQF0BVZLZi/hoB03oA2gIR0CUlt/kNnXedX2UKGgGR0Bj7U8La24NaAdN6ANoCEdAlJdpp8F6iXV9lChoBkdAZUk06YE4emgHTegDaAhHQJSk0GiYb851fZQoaAZHQGDJb1RLsa9oB03oA2gIR0CUq8C2+fyxdX2UKGgGR0BhbKmhufmLaAdN6ANoCEdAlK7BdyDIzXV9lChoBkdAX+vx4IKMN2gHTegDaAhHQJSz9oZhrnF1fZQoaAZHQF47qjrRjSZoB03oA2gIR0CUuVUkv9LpdX2UKGgGR0BhLNeSjgyeaAdN6ANoCEdAlMD5MxoIwHV9lChoBkdAYO31f3N9pmgHTegDaAhHQJTM++evpyJ1fZQoaAZHQGBON9QXQ+loB03oA2gIR0CU1ZlBhQWOdX2UKGgGR0BkIRxFRYRvaAdN6ANoCEdAlN0zURWcSXV9lChoBkdAZNMlWOp84WgHTegDaAhHQJTgIWO6unx1fZQoaAZHQF6SUyHmA9VoB03oA2gIR0CU4eFefI0ZdX2UKGgGR0BkqvO+qR2baAdN6ANoCEdAlPRKFIuoP3V9lChoBkdAYll/BnBciWgHTegDaAhHQJT0ieGwiaB1fZQoaAZHQF8K+yZ8a4toB03oA2gIR0CU+7vsJIDpdX2UKGgGR0BiHosXizcAaAdN6ANoCEdAlP1hEa2nbnV9lChoBkdAV6YSUTtb92gHTegDaAhHQJT+Akka/AV1fZQoaAZHQCc/fbblA/toB017AWgIR0CVCzqABkqddX2UKGgGR0Bf6ZblijL0aAdN6ANoCEdAlQ2F2JSBLHV9lChoBkdAQXD+98JD3WgHTVQBaAhHQJUPlmCiAUd1fZQoaAZHQGDIn9WIXTFoB03oA2gIR0CVFJv863iJdX2UKGgGR0BiOk5XEIgOaAdN6ANoCEdAlRfTbvgFYHV9lChoBkdAZKhQUpNKy2gHTegDaAhHQJUbU1rIo3J1fZQoaAZHQGWijxb0OExoB03oA2gIR0CVHqkLQXyidX2UKGgGR0BkCTNSqEOBaAdN6ANoCEdAlSOb6ciGFnV9lChoBkdAXXQo8ZDRdGgHTegDaAhHQJUrPiqABkt1fZQoaAZHQGCT2s7uDz1oB03oA2gIR0CVMX5sTFl1dX2UKGgGR0BePIsAeaKDaAdN6ANoCEdAlTo4T0xubnV9lChoBkdAX23Onl4keWgHTegDaAhHQJU74g+yJKt1fZQoaAZHQGdTYa5wwTNoB03oA2gIR0CVPbfpljEvdX2UKGgGR0BXq3kHUtqYaAdN6ANoCEdAlVxySmqHXXV9lChoBkdAY/0GDcuanmgHTegDaAhHQJVeRxwQ1791fZQoaAZHQGLmVhTfixVoB03oA2gIR0CVXv9du5z6dX2UKGgGR0BiXoPGyX2NaAdN6ANoCEdAlWl95dGAkXV9lChoBkdAYsc/0NBnjGgHTegDaAhHQJVrMNWluWN1fZQoaAZHQF97jhky1u1oB03oA2gIR0CVbMzhxYJWdX2UKGgGR0Bk8h/oaDPGaAdN6ANoCEdAlXB07KaG6HV9lChoBkdAYhSUJOWSlmgHTegDaAhHQJVykxcmjTN1fZQoaAZHQGCT1ENOM2poB03oA2gIR0CVdaOBDohZdX2UKGgGR0BdLYi9qUNbaAdN6ANoCEdAlXjBr30wrXV9lChoBkdAXLzNu+AVf2gHTegDaAhHQJV9bmjj7yh1fZQoaAZHQFtcfbKzRhNoB03oA2gIR0CVhLgpjMFEdX2UKGgGR0BagZAprk8zaAdN6ANoCEdAlYx9cjZ+QXV9lChoBkdAXrZ6nivPkmgHTegDaAhHQJWZ7NNahYh1fZQoaAZHQGMIvSMLncNoB03oA2gIR0CVnF4pMHrydX2UKGgGR0BeChwl0HQhaAdN6ANoCEdAlZ80jTrmhnV9lChoBkdAYFnp/PPcBWgHTegDaAhHQJW6HENvwVl1fZQoaAZHQGEDvbfxc3VoB03oA2gIR0CVu16ltTDPdX2UKGgGR0Be2wqiGnGbaAdN6ANoCEdAlbviOvMbFXV9lChoBkdAYRENEw35vmgHTegDaAhHQJXGPZcs1891fZQoaAZHQGHeymIj4YdoB03oA2gIR0CVyBqkuYhMdX2UKGgGR0BhrZ7LMcIaaAdN6ANoCEdAlcna0QbuMXV9lChoBkdAX2mqDK5kLGgHTegDaAhHQJXNvx6OYIB1fZQoaAZHQGJF94NZvDRoB03oA2gIR0CV0D3wCr93dX2UKGgGR0Bjyp2B8QZoaAdN6ANoCEdAldSxV+7UX3V9lChoBkdAZUxT4tYjjmgHTegDaAhHQJXZvSThYNl1fZQoaAZHQFzvLPldTpBoB03oA2gIR0CV4MeOXE61dX2UKGgGR0Bgl6Bun/DMaAdN6ANoCEdAlewIrBj4H3V9lChoBkdAWr9rFfiPyWgHTegDaAhHQJX07ZTQ3P11fZQoaAZHQGDz24Vh1DBoB03oA2gIR0CV/zwOOKfndX2UKGgGR0BhBeucMEzPaAdN6ANoCEdAlgEm8IzFdnV9lChoBkdAYMcegctGu2gHTegDaAhHQJYDMoVmBe51ZS4="}, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}