def __init__( self, device, name, pi=0.1, decimation_probability=0.5, local_search_iterations=0, epsilon=0.05, ): super(ReinforceSurveyPropagatorSolver, self).__init__( device=device, name=name, propagator=pdp_propagate.SurveyPropagator( device, decimator_dimension=1, include_adaptors=False, pi=pi ), decimator=pdp_decimate.ReinforceDecimator( device, scorer=pdp_predict.SurveyScorer( device, message_dimension=1, include_adaptors=False, pi=pi ), decimation_probability=decimation_probability, ), predictor=pdp_predict.ReinforcePredictor(device=device), local_search_iterations=local_search_iterations, epsilon=epsilon, )
def __init__(self, device, name, tolerance, t_max, local_search_iterations=0, epsilon=0.05): super(SurveyPropagatorSolver, self).__init__( device=device, name=name, propagator=pdp_propagate.SurveyPropagator(device, decimator_dimension=1, include_adaptors=False), decimator=pdp_decimate.SequentialDecimator( device, message_dimension=(3, 1), scorer=pdp_predict.SurveyScorer(device, message_dimension=1, include_adaptors=False), tolerance=tolerance, t_max=t_max), predictor=pdp_predict.IdentityPredictor(device=device, random_fill=True), local_search_iterations=local_search_iterations, epsilon=epsilon)