{
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        "__module__": "stable_baselines3.td3.policies",
        "__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    ",
        "__init__": "<function TD3Policy.__init__ at 0x7fe9b1522680>",
        "_build": "<function TD3Policy._build at 0x7fe9b1522710>",
        "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7fe9b15227a0>",
        "make_actor": "<function TD3Policy.make_actor at 0x7fe9b1522830>",
        "make_critic": "<function TD3Policy.make_critic at 0x7fe9b15228c0>",
        "forward": "<function TD3Policy.forward at 0x7fe9b1522950>",
        "_predict": "<function TD3Policy._predict at 0x7fe9b15229e0>",
        "set_training_mode": "<function TD3Policy.set_training_mode at 0x7fe9b1522a70>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7fe9b150ab70>"
    },
    "verbose": 0,
    "policy_kwargs": {},
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        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
        "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf]",
        "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]",
        "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
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        "bounded_below": "[ True  True  True  True]",
        "bounded_above": "[ True  True  True  True]",
        "_np_random": "RandomState(MT19937)"
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    "n_envs": 32,
    "num_timesteps": 29760000,
    "_total_timesteps": 50000000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
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    "learning_rate": 0.0001,
    "tensorboard_log": "model_log/",
    "lr_schedule": {
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    "ep_success_buffer": {
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        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
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    "_n_updates": 929984,
    "buffer_size": 1000000,
    "batch_size": 128,
    "learning_starts": 100,
    "tau": 0.005,
    "gamma": 0.999,
    "gradient_steps": 32,
    "optimize_memory_usage": false,
    "replay_buffer_class": {
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        "__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:\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    :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 0x7fe9b1502560>",
        "add": "<function ReplayBuffer.add at 0x7fe9b15025f0>",
        "sample": "<function ReplayBuffer.sample at 0x7fe9b1502680>",
        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fe9b1502710>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7fe9b1555ed0>"
    },
    "replay_buffer_kwargs": {},
    "train_freq": {
        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
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    },
    "use_sde_at_warmup": false,
    "policy_delay": 2,
    "target_noise_clip": 0.5,
    "target_policy_noise": 0.2
}