{"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 0x7f03974aa160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f03974aa1f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f03974aa280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f03974aa310>", "_build": "<function ActorCriticPolicy._build at 0x7f03974aa3a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f03974aa430>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f03974aa4c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f03974aa550>", "_predict": "<function ActorCriticPolicy._predict at 0x7f03974aa5e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f03974aa670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f03974aa700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f03974aa790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f03974a2e10>"}, "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": 1674336083599550913, "learning_rate": 0.00096, "tensorboard_log": null, "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:": "gAWVRAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQJl4MrAgxJyMAWyUTegDjAF0lEdArLugkE9t/HV9lChoBkdAmVVWOU+s5mgHTegDaAhHQKzA9SYPXkJ1fZQoaAZHQJk9Lv3JxNtoB03oA2gIR0CswhSJKraNdX2UKGgGR0CZiONNJvpAaAdN6ANoCEdArMKGCCjDbnV9lChoBkdAmUuNETg2qGgHTegDaAhHQKzH343WFvh1fZQoaAZHQJoxBdHDrJNoB03oA2gIR0CszXTxXnyNdX2UKGgGR0CZxXIwM6RyaAdN6ANoCEdArM6fV7Qb/HV9lChoBkdAlEey/CZWrGgHTegDaAhHQKzPA6oVEeB1fZQoaAZHQJrg56yB06poB03oA2gIR0Cs1FnbypaSdX2UKGgGR0CZ5iKnvUjLaAdN6ANoCEdArNnljgAIY3V9lChoBkdAmVjoqkM1CWgHTegDaAhHQKzbE6Ae7tl1fZQoaAZHQJhXiGoJiRZoB03oA2gIR0Cs2324EwFldX2UKGgGR0CXIZAmiQDFaAdN6ANoCEdArODuGO+7DnV9lChoBkdAmP/+HzpX62gHTegDaAhHQKzmTJKaodd1fZQoaAZHQJq/9z+3pfRoB03oA2gIR0Cs5282itaIdX2UKGgGR0Cax9YuCf6HaAdN6ANoCEdArOfRvR7Z4HV9lChoBkdAmYricTakAWgHTegDaAhHQKztMnO0LMN1fZQoaAZHQJrduxW1c+toB03oA2gIR0Cs8qSuIRAbdX2UKGgGR0CbUACFsYVJaAdN6ANoCEdArPPHyZrpJXV9lChoBkdAl/fBH9WIXWgHTegDaAhHQKz0K3AmAsl1fZQoaAZHQJe5WJYT0xxoB03oA2gIR0Cs+YOzhP0qdX2UKGgGR0CU2RqWC2+gaAdN6ANoCEdArP7gQpWmxnV9lChoBkdAlce6CDmKZWgHTegDaAhHQK0AHCEYfnx1fZQoaAZHQJZAwrCm/FloB03oA2gIR0CtAIRpUPxydX2UKGgGR0CZqUv/BFd+aAdN6ANoCEdArQXUvboKUnV9lChoBkdAmHby+UQkHGgHTegDaAhHQK0LMJWvKU51fZQoaAZHQJlLYzAN5MVoB03oA2gIR0CtDEzER8MNdX2UKGgGR0CZ24/io86naAdN6ANoCEdArQyv24/eL3V9lChoBkdAmIB4yCWeH2gHTegDaAhHQK0R9QZ4wAV1fZQoaAZHQJU0bBBRhttoB03oA2gIR0CtF2aPKdQPdX2UKGgGR0CZoMRw6ySnaAdN6ANoCEdArRiOdbxEv3V9lChoBkdAmh09rKvFFWgHTegDaAhHQK0Y8Nc4YJp1fZQoaAZHQJmZ8x+KCQNoB03oA2gIR0CtHkpEpiI+dX2UKGgGR0CX4w+iaiK0aAdN6ANoCEdArSOZiCrcTXV9lChoBkdAmO6uarmyPmgHTegDaAhHQK0kvPWxyGV1fZQoaAZHQJpX7HAAQxxoB03oA2gIR0CtJRyksSTRdX2UKGgGR0CaaeUVi4KAaAdN6ANoCEdArSqALThHb3V9lChoBkdAmtjMiB5HE2gHTegDaAhHQK0v5Z/Tb351fZQoaAZHQJmnSPuG9HtoB03oA2gIR0CtMQyGBWgfdX2UKGgGR0CZ4HjMFEApaAdN6ANoCEdArTFyz9jwx3V9lChoBkdAmNTwNCqp+GgHTegDaAhHQK023mbsniN1fZQoaAZHQJjDVb9qDbtoB03oA2gIR0CtPEZRCQcQdX2UKGgGR0Caz4yTY/VzaAdN6ANoCEdArT1n446wMnV9lChoBkdAmrNMIE8q4GgHTegDaAhHQK09zMbFS891fZQoaAZHQJi5uJemelNoB03oA2gIR0CtQx8RDkU9dX2UKGgGR0CagXx7RfF8aAdN6ANoCEdArUiKd1+y7nV9lChoBkdAmkARkAggYGgHTegDaAhHQK1JrsabWmR1fZQoaAZHQJl44Hmig01oB03oA2gIR0CtShFPBSDRdX2UKGgGR0Ca8Fn/1g6VaAdN6ANoCEdArU9rTUiIL3V9lChoBkdAm1TMtK7I1mgHTegDaAhHQK1U1sDW9UV1fZQoaAZHQJrGnIPsiStoB03oA2gIR0CtVgI5PuXvdX2UKGgGR0CaTgozvZyuaAdN6ANoCEdArVZqVv/BFnV9lChoBkdAm4YR/ZuhsmgHTegDaAhHQK1b4lGgBcR1fZQoaAZHQJtIVRpDeCVoB03oA2gIR0CtYVhKL877dX2UKGgGR0Cb6JLLIPsiaAdN6ANoCEdArWKBz1bqyHV9lChoBkdAm3bnZXdTHmgHTegDaAhHQK1i7BppN9J1fZQoaAZHQJtmud8Rcu9oB03oA2gIR0CtaEAhje9BdX2UKGgGR0CZIGR8MNMHaAdN6ANoCEdArW2w/PgNw3V9lChoBkdAml/lw97ngmgHTegDaAhHQK1u3PXTVlR1fZQoaAZHQJmDt57gKnhoB03oA2gIR0Ctb0lF+d9VdX2UKGgGR0CYDnipvP1MaAdN6ANoCEdArXS5jawljXV9lChoBkdAm7Dt0zTF2mgHTegDaAhHQK16Jz2exwB1fZQoaAZHQJnhs/OdGy5oB03oA2gIR0Cte0VAiV0LdX2UKGgGR0CassT3qRlpaAdN6ANoCEdArXuoy6+WW3V9lChoBkdAmvO265Gz8mgHTegDaAhHQK2BF5a/yoZ1fZQoaAZHQJh2aI3zcypoB03oA2gIR0CthqXirDIjdX2UKGgGR0CVwVtQKrq/aAdN6ANoCEdArYfI8uBczXV9lChoBkdAlCImITGo72gHTegDaAhHQK2IMC4Bmwt1fZQoaAZHQJtz/lEJBxBoB03oA2gIR0CtjY5GKAJ+dX2UKGgGR0CbMKahHskZaAdN6ANoCEdArZMZNbkfcXV9lChoBkdAmuElea8Yh2gHTegDaAhHQK2URg1FYuF1fZQoaAZHQJU3KbF0gbJoB03oA2gIR0CtlK+1rqMWdX2UKGgGR0CWsYT2FnIyaAdN6ANoCEdArZocIZ62OXV9lChoBkdAlL/e6RQrMGgHTegDaAhHQK2frENvwVl1fZQoaAZHQJhTl+fAbhpoB03oA2gIR0CtoNjoIOYqdX2UKGgGR0CW3UDyOJcgaAdN6ANoCEdAraE/hybQTnV9lChoBkdAmomzJyQxOGgHTegDaAhHQK2mmXBP9DR1fZQoaAZHQJsI83BHkLhoB03oA2gIR0Ctq/fub7TEdX2UKGgGR0CbUAxTsIE9aAdN6ANoCEdAra0aURnOB3V9lChoBkdAmuVaCDmKZWgHTegDaAhHQK2tf1M/QjV1fZQoaAZHQJwDHGcWj45oB03oA2gIR0Ctss2JaaCudX2UKGgGR0CYtbJv5xioaAdN6ANoCEdArbgw+2VmjHV9lChoBkdAm1aCCjDbamgHTegDaAhHQK25V2nKnvV1fZQoaAZHQJmLrKU3XI5oB03oA2gIR0CtucO8scyWdX2UKGgGR0CaMNmNR3vAaAdN6ANoCEdArb80Jng5znV9lChoBkdAm+9S5mRNh2gHTegDaAhHQK3Ep1FH8TB1fZQoaAZHQJrNqef7JnxoB03oA2gIR0Ctxb9pZfUndX2UKGgGR0Cb4obFS88LaAdN6ANoCEdArcYoIv8IiXV9lChoBkdAnEcpD/lyR2gHTegDaAhHQK3LboTwlSl1fZQoaAZHQJp4B+I/JNloB03oA2gIR0Ct0QeQEIPcdX2UKGgGR0CYmIw2VE/jaAdN6ANoCEdArdI1x+8XenV9lChoBkdAmGxb3PAwf2gHTegDaAhHQK3SnblA/s51fZQoaAZHQJpz4nBtUGVoB03oA2gIR0Ct1/a3y7PIdX2UKGgGR0CYOt5WilBQaAdN6ANoCEdArd1hnctXgnV9lChoBkdAmjWf99+gDmgHTegDaAhHQK3ehng5zYF1fZQoaAZHQJT0VDohY/5oB03oA2gIR0Ct3u4lpoK2dX2UKGgGR0CY858tf5UMaAdN6ANoCEdAreRBkEs8PnV9lChoBkdAmQePlIVdomgHTegDaAhHQK3poQOFxn51fZQoaAZHQJooOkAPuohoB03oA2gIR0Ct6sx+KCQLdX2UKGgGR0CaGCle4TbnaAdN6ANoCEdAresxkf9xZXVlLg=="}, "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-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}