{"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 0x7e9ae46137f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e9ae4613880>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e9ae4613910>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e9ae46139a0>", "_build": "<function ActorCriticPolicy._build at 0x7e9ae4613a30>", "forward": "<function ActorCriticPolicy.forward at 0x7e9ae4613ac0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e9ae4613b50>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e9ae4613be0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e9ae4613c70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e9ae4613d00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e9ae4613d90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e9ae4613e20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e9ae4618c00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710479742419639743, "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:": "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"}, "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}