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{
"policy_class": {
":type:": "<class 'abc.ABCMeta'>",
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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 0x7fc1a149e7a0>",
"_build": "<function TD3Policy._build at 0x7fc1a149e830>",
"_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7fc1a149e8c0>",
"make_actor": "<function TD3Policy.make_actor at 0x7fc1a149e950>",
"make_critic": "<function TD3Policy.make_critic at 0x7fc1a149e9e0>",
"forward": "<function TD3Policy.forward at 0x7fc1a149ea70>",
"_predict": "<function TD3Policy._predict at 0x7fc1a149eb00>",
"set_training_mode": "<function TD3Policy.set_training_mode at 0x7fc1a149eb90>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7fc1a14917b0>"
},
"verbose": 1,
"policy_kwargs": {
"n_critics": 1
},
"observation_space": {
":type:": "<class 'gym.spaces.box.Box'>",
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"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]",
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