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        "__module__": "stable_baselines3.sac.policies",
        "__doc__": "\n    Policy class (with both actor and critic) for SAC.\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 use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` when using gSDE 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 clip_mean: Clip the mean output when using gSDE to avoid numerical instability.\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 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    :param n_critics: Number of critic networks to create.\n    :param share_features_extractor: Whether to share or not the features extractor\n        between the actor and the critic (this saves computation time)\n    ",
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        "_build": "<function SACPolicy._build at 0x7f2cf3dd2d30>",
        "_get_constructor_parameters": "<function SACPolicy._get_constructor_parameters at 0x7f2cf3dd2dc0>",
        "reset_noise": "<function SACPolicy.reset_noise at 0x7f2cf3dd2e50>",
        "make_actor": "<function SACPolicy.make_actor at 0x7f2cf3dd2ee0>",
        "make_critic": "<function SACPolicy.make_critic at 0x7f2cf3dd2f70>",
        "forward": "<function SACPolicy.forward at 0x7f2cf3dda040>",
        "_predict": "<function SACPolicy._predict at 0x7f2cf3dda0d0>",
        "set_training_mode": "<function SACPolicy.set_training_mode at 0x7f2cf3dda160>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7f2cf3dd6f40>"
    },
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        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf]",
        "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf]",
        "bounded_below": "[False False False False False False False False False False False False\n False False False]",
        "bounded_above": "[False False False False False False False False False False False False\n False False False]",
        "_np_random": null
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    "ent_coef": "auto",
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    "_action_repeat": [
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    "surgeon": null,
    "batch_norm_stats": [],
    "batch_norm_stats_target": [],
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}