{
    "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 0x7f18d73d0d30>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f18d73d0dc0>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f18d73d0e50>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f18d73d0ee0>",
        "_build": "<function ActorCriticPolicy._build at 0x7f18d73d0f70>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f18d73d3040>",
        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f18d73d30d0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f18d73d3160>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f18d73d31f0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f18d73d3280>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f18d73d3310>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f18d73d33a0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7f18d73cea40>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            3
        ],
        "low": "[-1. -1. -8.]",
        "high": "[1. 1. 8.]",
        "bounded_below": "[ True  True  True]",
        "bounded_above": "[ True  True  True]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            1
        ],
        "low": "[-2.]",
        "high": "[2.]",
        "bounded_below": "[ True]",
        "bounded_above": "[ True]",
        "_np_random": "RandomState(MT19937)"
    },
    "n_envs": 1,
    "num_timesteps": 100352,
    "_total_timesteps": 100000,
    "_num_timesteps_at_start": 0,
    "seed": 0,
    "action_noise": null,
    "start_time": 1670945697178679686,
    "learning_rate": 0.001,
    "tensorboard_log": "runs/Pendulum-v1__trpo__3955154760__1670945694/Pendulum-v1",
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "_last_obs": null,
    "_last_episode_starts": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVdQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYCAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksChZSMAUOUdJRSlC4="
    },
    "_last_original_obs": null,
    "_episode_num": 0,
    "use_sde": true,
    "sde_sample_freq": 4,
    "_current_progress_remaining": -0.0035199999999999676,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 49,
    "n_steps": 1024,
    "gamma": 0.9,
    "gae_lambda": 0.95,
    "ent_coef": 0.0,
    "vf_coef": 0.0,
    "max_grad_norm": 0.0,
    "normalize_advantage": true,
    "batch_size": 128,
    "cg_max_steps": 15,
    "cg_damping": 0.1,
    "line_search_shrinking_factor": 0.8,
    "line_search_max_iter": 10,
    "target_kl": 0.01,
    "n_critic_updates": 15,
    "sub_sampling_factor": 1
}