{"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 0x7f51adc83490>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f51adc83520>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f51adc835b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f51adc83640>", "_build": "<function ActorCriticPolicy._build at 0x7f51adc836d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f51adc83760>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f51adc837f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f51adc83880>", "_predict": "<function ActorCriticPolicy._predict at 0x7f51adc83910>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f51adc839a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f51adc83a30>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f51adc83ac0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f51adc735c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1687876859288265651, "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:": "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 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"}}