This module contains the loggers that can be used with the optimization drivers by passing them to the out= keyword argument of run().

Inheritance diagram of netket.logging, netket.experimental.logging

The base class follows the API protocol declared here. You should reimplement this class to make a logger that works well together with our drivers.


Abstract base class detailing the interface that loggers must implement in order to work with netket drivers.

While the loggers available for simulations are the following:


This logger accumulates log data in a set of nested dictionaries which are stored in memory.


This logger serializes expectation values and other log data to a JSON file and can save the latest model parameters in MessagePack encoding to a separate file.


A logger which serializes the variables of the variational state during a run.


Creates a tensorboard logger using tensorboardX's summarywriter.

In the netket.experimental module there are also some experimental loggers such as the HDF5 logger