{
    "policy_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=",
        "__module__": "stable_baselines3.dqn.policies",
        "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}",
        "__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    ",
        "__init__": "<function DQNPolicy.__init__ at 0x7f4dcefc8790>",
        "_build": "<function DQNPolicy._build at 0x7f4dcefc8820>",
        "make_q_net": "<function DQNPolicy.make_q_net at 0x7f4dcefc88b0>",
        "forward": "<function DQNPolicy.forward at 0x7f4dcefc8940>",
        "_predict": "<function DQNPolicy._predict at 0x7f4dcefc89d0>",
        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7f4dcefc8a60>",
        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7f4dcefc8af0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7f4dcefbb840>"
    },
    "verbose": 1,
    "policy_kwargs": {
        "net_arch": [
            256,
            256
        ]
    },
    "num_timesteps": 30000,
    "_total_timesteps": 50000,
    "_num_timesteps_at_start": 0,
    "seed": 0,
    "action_noise": null,
    "start_time": 1699149376068469832,
    "learning_rate": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "tensorboard_log": "runs/CartPole-v1__dqn__2652168140__1699149373/CartPole-v1",
    "_last_obs": null,
    "_last_episode_starts": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
    },
    "_last_original_obs": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVhQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAACh7/z7bw5M8GP0HvMGnDz2UjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLBIaUjAFDlHSUUpQu"
    },
    "_episode_num": 388,
    "use_sde": false,
    "sde_sample_freq": -1,
    "_current_progress_remaining": 0.40002000000000004,
    "_stats_window_size": 100,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 14592,
    "observation_space": {
        ":type:": "<class 'gymnasium.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "bounded_below": "[ True  True  True  True]",
        "bounded_above": "[ True  True  True  True]",
        "_shape": [
            4
        ],
        "low": "[-4.8000002e+00 -3.4028235e+38 -4.1887903e-01 -3.4028235e+38]",
        "high": "[4.8000002e+00 3.4028235e+38 4.1887903e-01 3.4028235e+38]",
        "low_repr": "[-4.8000002e+00 -3.4028235e+38 -4.1887903e-01 -3.4028235e+38]",
        "high_repr": "[4.8000002e+00 3.4028235e+38 4.1887903e-01 3.4028235e+38]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
        ":serialized:": "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",
        "n": "2",
        "start": "0",
        "_shape": [],
        "dtype": "int64",
        "_np_random": "Generator(PCG64)"
    },
    "n_envs": 1,
    "buffer_size": 1,
    "batch_size": 64,
    "learning_starts": 1000,
    "tau": 1.0,
    "gamma": 0.99,
    "gradient_steps": 128,
    "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 0x7f4dcefa8f70>",
        "add": "<function ReplayBuffer.add at 0x7f4dcefa9000>",
        "sample": "<function ReplayBuffer.sample at 0x7f4dcefa9090>",
        "_get_samples": "<function ReplayBuffer._get_samples at 0x7f4dcefa9120>",
        "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x7f4dcefa91b0>)>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7f4dcf3ca7c0>"
    },
    "replay_buffer_kwargs": {},
    "train_freq": {
        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
        ":serialized:": "gAWVYgAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RNAAFoAIwSVHJhaW5GcmVxdWVuY3lVbml0lJOUjARzdGVwlIWUUpSGlIGULg=="
    },
    "use_sde_at_warmup": false,
    "exploration_initial_eps": 1.0,
    "exploration_final_eps": 0.04,
    "exploration_fraction": 0.16,
    "target_update_interval": 10,
    "_n_calls": 29999,
    "max_grad_norm": 10,
    "exploration_rate": 0.04,
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "batch_norm_stats": [],
    "batch_norm_stats_target": [],
    "exploration_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    }
}