mbi.callbacks

Defines callback mechanisms for monitoring optimization processes.

This module provides a Callback class that can be used to track and log various metrics during iterative algorithms, such as those used in estimating marginals. It logs loss values and other relevant statistics.

Functions

default

Creates a default Callback with standard loss functions (L1/L2 Loss/Error, Primal Feas).

Classes

Callback

Method generated by attrs for class Callback.

class mbi.callbacks.Callback(loss_fns: dict[str, MarginalLossFn], frequency: int = 50, step: int = 0, logs: list = NOTHING)[source]

Bases: object

Method generated by attrs for class Callback.

loss_fns: dict[str, MarginalLossFn]

frequency: int

property summary

mbi.callbacks.default(measurements: list[LinearMeasurement], data: Projectable | None = None, frequency: int = 50) → Callback[source]: Creates a default Callback with standard loss functions (L1/L2 Loss/Error, Primal Feas).