org.deeplearning4j.optimize.listeners

Class ParamAndGradientIterationListener

java.lang.Object

org.deeplearning4j.optimize.api.BaseTrainingListener

org.deeplearning4j.optimize.listeners.ParamAndGradientIterationListener

All Implemented Interfaces:

TrainingListener

Deprecated.

StatsListener can be used instead, storing data using FileStatsStorage - UI is not required

public class ParamAndGradientIterationListener
extends BaseTrainingListener

An iteration listener that provides details on parameters and gradients at each iteration during traning. Attempts to provide much of the same information as the UI histogram iteration listener, but in a text-based format (for example, when learning on a system accessed via SSH etc). i.e., is intended to aid network tuning and debugging
This iteration listener is set up to calculate mean, min, max, and mean absolute value of each type of parameter and gradient in the network at each iteration.

Author:

Alex Black

Constructor Summary

Constructors

Constructor and Description
ParamAndGradientIterationListener() Deprecated. Default constructor for output to console only every iteration, tab delimited
ParamAndGradientIterationListener(int iterations, boolean printHeader, boolean printMean, boolean printMinMax, boolean printMeanAbsValue, boolean outputToConsole, boolean outputToFile, boolean outputToLogger, File file, String delimiter) Deprecated. Full constructor with all options.

Method Summary

Modifier and Type	Method and Description
void	iterationDone(Model model, int iteration, int epoch) Deprecated. Event listener for each iteration.

Methods inherited from class org.deeplearning4j.optimize.api.BaseTrainingListener

onBackwardPass, onEpochEnd, onEpochStart, onForwardPass, onForwardPass, onGradientCalculation

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ParamAndGradientIterationListener

public ParamAndGradientIterationListener()

Deprecated.

Default constructor for output to console only every iteration, tab delimited

ParamAndGradientIterationListener

public ParamAndGradientIterationListener(int iterations,
                                         boolean printHeader,
                                         boolean printMean,
                                         boolean printMinMax,
                                         boolean printMeanAbsValue,
                                         boolean outputToConsole,
                                         boolean outputToFile,
                                         boolean outputToLogger,
                                         File file,
                                         String delimiter)

Deprecated.

Full constructor with all options. Note also: ParamAndGradientIterationListener.builder() can be used instead of this constructor.

Parameters:

iterations - calculate and report values every 'iterations' iterations

printHeader - Whether to output a header row (i.e., names for each column)

printMean - Calculate and display the mean of parameters and gradients

printMinMax - Calculate and display the min/max of the parameters and gradients

printMeanAbsValue - Calculate and display the mean absolute value

outputToConsole - If true, display the values to the console (System.out.println())

outputToFile - If true, write the values to a file, one per line

outputToLogger - If true, log the values

file - File to write values to. May be null, not used if outputToFile == false

delimiter - delimiter (for example, "\t" or "," etc)

Method Detail

iterationDone

public void iterationDone(Model model,
                          int iteration,
                          int epoch)

Deprecated.

Description copied from interface: TrainingListener

Event listener for each iteration. Called once, after each parameter update has ocurred while training the network

Specified by:

iterationDone in interface TrainingListener

Overrides:

iterationDone in class BaseTrainingListener

Parameters:

model - the model iterating

iteration - the iteration