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    "batch_size": 32,
    "learning_starts": 50000,
    "tau": 1.0,
    "gamma": 0.99,
    "gradient_steps": 1,
    "optimize_memory_usage": false,
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        "__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    ",
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        "add": "<function ReplayBuffer.add at 0x7fb7ef5b03b0>",
        "sample": "<function ReplayBuffer.sample at 0x7fb7ef5b0440>",
        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fb7ef5b04d0>",
        "__abstractmethods__": "frozenset()",
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    "replay_buffer_kwargs": {},
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    "actor": null,
    "use_sde_at_warmup": false,
    "exploration_initial_eps": 1.0,
    "exploration_final_eps": 0.05,
    "exploration_fraction": 0.1,
    "target_update_interval": 625,
    "_n_calls": 31252,
    "max_grad_norm": 10,
    "exploration_rate": 0.05,
    "exploration_schedule": {
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}