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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: 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 0x327136f70>",
"add": "<function ReplayBuffer.add at 0x327143040>",
"sample": "<function ReplayBuffer.sample at 0x3271430d0>",
"_get_samples": "<function ReplayBuffer._get_samples at 0x327143160>",
"_maybe_cast_dtype": "<staticmethod object at 0x327137af0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x326eff980>"
},
"replay_buffer_kwargs": {},
"train_freq": {
":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
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},
"use_sde_at_warmup": false,
"exploration_initial_eps": 1.0,
"exploration_final_eps": 0.05,
"exploration_fraction": 0.1,
"target_update_interval": 10000,
"_n_calls": 1000,
"max_grad_norm": 10,
"exploration_rate": 0.05,
"lr_schedule": {
":type:": "<class 'function'>",
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},
"batch_norm_stats": [],
"batch_norm_stats_target": [],
"exploration_schedule": {
":type:": "<class 'function'>",
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}
} |