{"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 0x7e6db3282170>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e6db3282200>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e6db3282290>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e6db3282320>", "_build": "<function ActorCriticPolicy._build at 0x7e6db32823b0>", "forward": "<function ActorCriticPolicy.forward at 0x7e6db3282440>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e6db32824d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e6db3282560>", "_predict": "<function ActorCriticPolicy._predict at 0x7e6db32825f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e6db3282680>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e6db3282710>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e6db32827a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e6db327b100>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1689769680969223736, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAALpdK74CQwU/9iM6Pjyopr5s/IE99vw4OwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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-5.15.109+-x86_64-with-glibc2.31 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "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"}}