tqc-PandaReachDense-v2 / config.json
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In practice, ``exp()`` is usually enough.\n :param clip_mean: Clip the mean output when using gSDE to avoid numerical instability.\n :param features_extractor_class: Features extractor to use.\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_quantiles: Number of quantiles for the critic.\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 MultiInputPolicy.__init__ at 0x7f29c62d6290>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f29c627dd80>"}, "verbose": 1, "policy_kwargs": {"net_arch": [64, 64], "n_critics": 1, "use_sde": 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