syne_tune.optimizer.schedulers.transfer_learning.transfer_learning_mixin module

class syne_tune.optimizer.schedulers.transfer_learning.transfer_learning_mixin.TransferLearningMixin(config_space, transfer_learning_evaluations, metric, random_seed=None, **kwargs)

Bases: object

top_k_hyperparameter_configurations_per_task(transfer_learning_evaluations, num_hyperparameters_per_task, do_minimize=False)

Returns the best hyperparameter configurations for each task. :type transfer_learning_evaluations: Dict[str, TransferLearningTaskEvaluations] :param transfer_learning_evaluations: Set of candidates to choose from. :type num_hyperparameters_per_task: int :param num_hyperparameters_per_task: The number of top hyperparameters per task to return. :type do_minimize: bool :param do_minimize: indicating if the optimization problem is minimized. :rtype: Dict[str, List[Dict[str, Any]]] :returns: Dict which maps from task name to list of hyperparameters in order.