{
    "policy_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVKgAAAAAAAACMGHNiM19jb250cmliLnRxYy5wb2xpY2llc5SMCVRRQ1BvbGljeZSTlC4=",
        "__module__": "sb3_contrib.tqc.policies",
        "__doc__": "\n    Policy class (with both actor and critic) for TQC.\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 feature 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_quantiles: Number of quantiles for the critic.\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    ",
        "__init__": "<function TQCPolicy.__init__ at 0x7fe7094ea670>",
        "_build": "<function TQCPolicy._build at 0x7fe7094ea700>",
        "_get_constructor_parameters": "<function TQCPolicy._get_constructor_parameters at 0x7fe7094ea790>",
        "reset_noise": "<function TQCPolicy.reset_noise at 0x7fe7094ea820>",
        "make_actor": "<function TQCPolicy.make_actor at 0x7fe7094ea8b0>",
        "make_critic": "<function TQCPolicy.make_critic at 0x7fe7094ea940>",
        "forward": "<function TQCPolicy.forward at 0x7fe7094ea9d0>",
        "_predict": "<function TQCPolicy._predict at 0x7fe7094eaa60>",
        "set_training_mode": "<function TQCPolicy.set_training_mode at 0x7fe7094eaaf0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7fe7094e8c00>"
    },
    "verbose": 1,
    "policy_kwargs": {
        "use_sde": false
    },
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float64",
        "_shape": [
            8
        ],
        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
        "high": "[inf inf inf inf inf inf inf inf]",
        "bounded_below": "[False False False False False False False False]",
        "bounded_above": "[False False False False False False False False]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            2
        ],
        "low": "[-1. -1.]",
        "high": "[1. 1.]",
        "bounded_below": "[ True  True]",
        "bounded_above": "[ True  True]",
        "_np_random": "RandomState(MT19937)"
    },
    "n_envs": 1,
    "num_timesteps": 1000000,
    "_total_timesteps": 1000000,
    "_num_timesteps_at_start": 0,
    "seed": 0,
    "action_noise": null,
    "start_time": 1676662682571112069,
    "learning_rate": 0.0003,
    "tensorboard_log": "runs/Swimmer-v3__tqc__3179311325__1676662679/Swimmer-v3",
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "_last_obs": null,
    "_last_episode_starts": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
    },
    "_last_original_obs": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVtQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZAAAAAAAAAAMQBAUlKTy1Ag0MQjfhF+79/QJBQa/P7v4fL6v0Rxdy/yGHTfxQjs7+wBb6VIWTmv/nXb376xPA/Q0raLHoWdr+UjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLCIaUjAFDlHSUUpQu"
    },
    "_episode_num": 1000,
    "use_sde": false,
    "sde_sample_freq": -1,
    "_current_progress_remaining": 0.0,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 990000,
    "buffer_size": 1,
    "batch_size": 256,
    "learning_starts": 10000,
    "tau": 0.005,
    "gamma": 0.9999,
    "gradient_steps": 1,
    "optimize_memory_usage": false,
    "replay_buffer_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
        "__module__": "stable_baselines3.common.buffers",
        "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
        "__init__": "<function ReplayBuffer.__init__ at 0x7fe7096ed5e0>",
        "add": "<function ReplayBuffer.add at 0x7fe7096ed670>",
        "sample": "<function ReplayBuffer.sample at 0x7fe7096ed700>",
        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fe7096ed790>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7fe7096e4f00>"
    },
    "replay_buffer_kwargs": {},
    "train_freq": {
        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
        ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
    },
    "use_sde_at_warmup": false,
    "target_entropy": -2.0,
    "ent_coef": "auto",
    "target_update_interval": 1,
    "top_quantiles_to_drop_per_net": 2,
    "batch_norm_stats": [],
    "batch_norm_stats_target": []
}