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{
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"__module__": "sb3_contrib.qrdqn.policies",
"__doc__": "\n Policy class with quantile and target networks for QR-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 n_quantiles: Number of quantiles\n :param net_arch: The specification of the network architecture.\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 QRDQNPolicy.__init__ at 0x7f48962d3820>",
"_build": "<function QRDQNPolicy._build at 0x7f48962d38b0>",
"make_quantile_net": "<function QRDQNPolicy.make_quantile_net at 0x7f48962d3940>",
"forward": "<function QRDQNPolicy.forward at 0x7f48962d39d0>",
"_predict": "<function QRDQNPolicy._predict at 0x7f48962d3a60>",
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"set_training_mode": "<function QRDQNPolicy.set_training_mode at 0x7f48962d3b80>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7f48962d6800>"
},
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"optimizer_kwargs": {
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"bounded_below": "[ True True True True True True]",
"bounded_above": "[ True True True True True True]",
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},
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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: 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 ",
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"__abstractmethods__": "frozenset()",
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},
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} |