Module laplace.laplace

Functions

def Laplace(model: torch.nn.Module, likelihood: Likelihood | str, subset_of_weights: SubsetOfWeights | str = SubsetOfWeights.LAST_LAYER, hessian_structure: HessianStructure | str = HessianStructure.KRON, *args, **kwargs)

Simplified Laplace access using strings instead of different classes.

Parameters

model : torch.nn.Module

 

likelihood : Likelihood or str in {'classification', 'regression'}

 

subset_of_weights : SubsetofWeights or {'last_layer', 'subnetwork', 'all'}, default=SubsetOfWeights.LAST_LAYER

subset of weights to consider for inference

hessian_structure : HessianStructure or str in {'diag', 'kron', 'full', 'lowrank', 'gp'}, default=HessianStructure.KRON

structure of the Hessian approximation (note that in case of 'gp', we are not actually doing any Hessian approximation, the inference is instead done in the functional space)

Returns

laplace : BaseLaplace

chosen subclass of BaseLaplace instantiated with additional arguments