{"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 0x78a816bcc3a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78a816bcc430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78a816bcc4c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78a816bcc550>", "_build": "<function ActorCriticPolicy._build at 0x78a816bcc5e0>", "forward": "<function ActorCriticPolicy.forward at 0x78a816bcc670>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78a816bcc700>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78a816bcc790>", "_predict": "<function ActorCriticPolicy._predict at 0x78a816bcc820>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78a816bcc8b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78a816bcc940>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78a816bcc9d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78a816bc4c80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1693474011331627169, "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-5.15.109+-x86_64-with-glibc2.35 # 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": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}