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        "__module__": "stable_baselines3.td3.policies",
        "__annotations__": "{'actor': <class 'stable_baselines3.td3.policies.Actor'>, 'actor_target': <class 'stable_baselines3.td3.policies.Actor'>, 'critic': <class 'stable_baselines3.common.policies.ContinuousCritic'>, 'critic_target': <class 'stable_baselines3.common.policies.ContinuousCritic'>}",
        "__doc__": "\n    Policy class (with both actor and critic) for TD3.\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 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 TD3Policy._build at 0x7ae480dae560>",
        "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7ae480dae5f0>",
        "make_actor": "<function TD3Policy.make_actor at 0x7ae480dae680>",
        "make_critic": "<function TD3Policy.make_critic at 0x7ae480dae710>",
        "forward": "<function TD3Policy.forward at 0x7ae480dae7a0>",
        "_predict": "<function TD3Policy._predict at 0x7ae480dae830>",
        "set_training_mode": "<function TD3Policy.set_training_mode at 0x7ae480dae8c0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7ae480db0b40>"
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        "_mu": "[0. 0. 0. 0. 0. 0.]",
        "_sigma": "[0.1 0.1 0.1 0.1 0.1 0.1]"
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    "actor_batch_norm_stats_target": [],
    "critic_batch_norm_stats_target": []
}