{"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 0x7f8441549ab0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8441549b40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8441549bd0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8441549c60>", "_build": "<function ActorCriticPolicy._build at 0x7f8441549cf0>", "forward": "<function ActorCriticPolicy.forward at 0x7f8441549d80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8441549e10>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8441549ea0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8441549f30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8441549fc0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f844154a050>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f844154a0e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f844154d200>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1686198131354434459, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAJptz73Ym6Q/R3y2vrWWdb4nzyi+FWqAvgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "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": "Generator(PCG64)"}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "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"}}