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        "__doc__": "\n    Policy class with Q-Value Net and target net for DQN\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    ",
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        "bounded_above": "[False False False False False False False False]",
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        "__abstractmethods__": "frozenset()",
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    "exploration_initial_eps": 1.0,
    "exploration_final_eps": 0.01,
    "exploration_fraction": 0.1,
    "target_update_interval": 3,
    "_n_calls": 62500,
    "max_grad_norm": 10,
    "exploration_rate": 0.01,
    "exploration_schedule": {
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    "batch_norm_stats": [],
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}