Uses of Interface
org.deeplearning4j.optimize.api.TrainingListener

Packages that use TrainingListener

Package	Description
org.deeplearning4j.nn.api
org.deeplearning4j.nn.conf.layers
org.deeplearning4j.nn.conf.layers.convolutional
org.deeplearning4j.nn.conf.layers.misc
org.deeplearning4j.nn.conf.layers.objdetect
org.deeplearning4j.nn.conf.layers.recurrent
org.deeplearning4j.nn.conf.layers.samediff
org.deeplearning4j.nn.conf.layers.util
org.deeplearning4j.nn.conf.layers.variational
org.deeplearning4j.nn.conf.ocnn
org.deeplearning4j.nn.graph
org.deeplearning4j.nn.layers
org.deeplearning4j.nn.layers.normalization
org.deeplearning4j.nn.layers.recurrent
org.deeplearning4j.nn.layers.variational
org.deeplearning4j.nn.layers.wrapper
org.deeplearning4j.nn.multilayer
org.deeplearning4j.optimize
org.deeplearning4j.optimize.api
org.deeplearning4j.optimize.listeners
org.deeplearning4j.optimize.solvers

Uses of TrainingListener in org.deeplearning4j.nn.api

Methods in org.deeplearning4j.nn.api that return types with arguments of type TrainingListener

Modifier and Type	Method and Description
Collection<TrainingListener>	Layer.getListeners() Get the iteration listeners for this layer.

Methods in org.deeplearning4j.nn.api with parameters of type TrainingListener

Modifier and Type	Method and Description
void	Model.addListeners(TrainingListener... listener) This method ADDS additional TrainingListener to existing listeners
void	Model.setListeners(TrainingListener... listeners) Set the trainingListeners for the ComputationGraph (and all layers in the network)
void	Layer.setListeners(TrainingListener... listeners) Set the TrainingListeners for this model.

Method parameters in org.deeplearning4j.nn.api with type arguments of type TrainingListener

Modifier and Type	Method and Description
void	Model.setListeners(Collection<TrainingListener> listeners) Set the trainingListeners for the ComputationGraph (and all layers in the network)
void	Layer.setListeners(Collection<TrainingListener> listeners) Set the TrainingListeners for this model.

Uses of TrainingListener in org.deeplearning4j.nn.conf.layers

Method parameters in org.deeplearning4j.nn.conf.layers with type arguments of type TrainingListener

Modifier and Type	Method and Description
Layer	Convolution3D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> iterationListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	DepthwiseConvolution2D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	RnnOutputLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	ConvolutionLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Upsampling1D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	LossLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	EmbeddingSequenceLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	RnnLossLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Deconvolution3D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	DenseLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	LocalResponseNormalization.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	CenterLossOutputLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Convolution1DLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Subsampling1DLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	EmbeddingLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Upsampling3D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> iterationListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	SubsamplingLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	GravesLSTM.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType) Deprecated.
Layer	Subsampling3DLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> iterationListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	ZeroPadding1DLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	DropoutLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	GravesBidirectionalLSTM.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType) Deprecated.
Layer	LSTM.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	SpaceToBatchLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	ActivationLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Deconvolution2D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	BatchNormalization.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Upsampling2D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	OutputLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	ZeroPadding3DLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> iterationListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	SpaceToDepthLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	GlobalPoolingLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Cnn3DLossLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
abstract Layer	Layer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	ZeroPaddingLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	AutoEncoder.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	CnnLossLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	PReLULayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	SeparableConvolution2D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Uses of TrainingListener in org.deeplearning4j.nn.conf.layers.convolutional

Method parameters in org.deeplearning4j.nn.conf.layers.convolutional with type arguments of type TrainingListener

Modifier and Type	Method and Description
Layer	Cropping2D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Cropping3D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> iterationListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Cropping1D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Uses of TrainingListener in org.deeplearning4j.nn.conf.layers.misc

Method parameters in org.deeplearning4j.nn.conf.layers.misc with type arguments of type TrainingListener

Modifier and Type	Method and Description
Layer	RepeatVector.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	FrozenLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	FrozenLayerWithBackprop.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	ElementWiseMultiplicationLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Uses of TrainingListener in org.deeplearning4j.nn.conf.layers.objdetect

Method parameters in org.deeplearning4j.nn.conf.layers.objdetect with type arguments of type TrainingListener

Modifier and Type	Method and Description
Layer	Yolo2OutputLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Uses of TrainingListener in org.deeplearning4j.nn.conf.layers.recurrent

Method parameters in org.deeplearning4j.nn.conf.layers.recurrent with type arguments of type TrainingListener

Modifier and Type	Method and Description
Layer	Bidirectional.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	TimeDistributed.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	LastTimeStep.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	SimpleRnn.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Uses of TrainingListener in org.deeplearning4j.nn.conf.layers.samediff

Method parameters in org.deeplearning4j.nn.conf.layers.samediff with type arguments of type TrainingListener

Modifier and Type	Method and Description
Layer	SameDiffLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	SameDiffOutputLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
abstract Layer	AbstractSameDiffLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Uses of TrainingListener in org.deeplearning4j.nn.conf.layers.util

Method parameters in org.deeplearning4j.nn.conf.layers.util with type arguments of type TrainingListener

Modifier and Type	Method and Description
Layer	MaskZeroLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	MaskLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Uses of TrainingListener in org.deeplearning4j.nn.conf.layers.variational

Method parameters in org.deeplearning4j.nn.conf.layers.variational with type arguments of type TrainingListener

Modifier and Type	Method and Description
Layer	VariationalAutoencoder.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Uses of TrainingListener in org.deeplearning4j.nn.conf.ocnn

Method parameters in org.deeplearning4j.nn.conf.ocnn with type arguments of type TrainingListener

Modifier and Type	Method and Description
Layer	OCNNOutputLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Uses of TrainingListener in org.deeplearning4j.nn.graph

Methods in org.deeplearning4j.nn.graph that return types with arguments of type TrainingListener

Modifier and Type	Method and Description
Collection<TrainingListener>	ComputationGraph.getListeners() Get the trainingListeners for the ComputationGraph

Methods in org.deeplearning4j.nn.graph with parameters of type TrainingListener

Modifier and Type	Method and Description
void	ComputationGraph.addListeners(TrainingListener... listeners) This method ADDS additional TrainingListener to existing listeners
void	ComputationGraph.setListeners(TrainingListener... listeners) Set the trainingListeners for the ComputationGraph (and all layers in the network)

Method parameters in org.deeplearning4j.nn.graph with type arguments of type TrainingListener

Modifier and Type	Method and Description
void	ComputationGraph.setListeners(Collection<TrainingListener> listeners) Set the trainingListeners for the ComputationGraph (and all layers in the network)

Uses of TrainingListener in org.deeplearning4j.nn.layers

Fields in org.deeplearning4j.nn.layers with type parameters of type TrainingListener

Modifier and Type	Field and Description
protected Collection<TrainingListener>	AbstractLayer.trainingListeners

Methods in org.deeplearning4j.nn.layers that return types with arguments of type TrainingListener

Modifier and Type	Method and Description
Collection<TrainingListener>	AbstractLayer.getListeners()

Methods in org.deeplearning4j.nn.layers with parameters of type TrainingListener

Modifier and Type	Method and Description
void	AbstractLayer.addListeners(TrainingListener... listeners) This method ADDS additional TrainingListener to existing listeners
void	AbstractLayer.setListeners(TrainingListener... listeners)

Method parameters in org.deeplearning4j.nn.layers with type arguments of type TrainingListener

Modifier and Type	Method and Description
void	AbstractLayer.setListeners(Collection<TrainingListener> listeners)

Uses of TrainingListener in org.deeplearning4j.nn.layers.normalization

Fields in org.deeplearning4j.nn.layers.normalization with type parameters of type TrainingListener

Modifier and Type	Field and Description
protected List<TrainingListener>	BatchNormalization.listeners

Methods in org.deeplearning4j.nn.layers.normalization that return types with arguments of type TrainingListener

Modifier and Type	Method and Description
Collection<TrainingListener>	BatchNormalization.getListeners()

Methods in org.deeplearning4j.nn.layers.normalization with parameters of type TrainingListener

Modifier and Type	Method and Description
void	BatchNormalization.setListeners(TrainingListener... listeners)

Uses of TrainingListener in org.deeplearning4j.nn.layers.recurrent

Methods in org.deeplearning4j.nn.layers.recurrent that return types with arguments of type TrainingListener

Modifier and Type	Method and Description
Collection<TrainingListener>	BidirectionalLayer.getListeners()

Methods in org.deeplearning4j.nn.layers.recurrent with parameters of type TrainingListener

Modifier and Type	Method and Description
void	BidirectionalLayer.addListeners(TrainingListener... listener)
void	BidirectionalLayer.setListeners(TrainingListener... listeners)

Method parameters in org.deeplearning4j.nn.layers.recurrent with type arguments of type TrainingListener

Modifier and Type	Method and Description
void	BidirectionalLayer.setListeners(Collection<TrainingListener> listeners)

Uses of TrainingListener in org.deeplearning4j.nn.layers.variational

Fields in org.deeplearning4j.nn.layers.variational with type parameters of type TrainingListener

Modifier and Type	Field and Description
protected Collection<TrainingListener>	VariationalAutoencoder.trainingListeners

Methods in org.deeplearning4j.nn.layers.variational that return types with arguments of type TrainingListener

Modifier and Type	Method and Description
Collection<TrainingListener>	VariationalAutoencoder.getListeners()

Methods in org.deeplearning4j.nn.layers.variational with parameters of type TrainingListener

Modifier and Type	Method and Description
void	VariationalAutoencoder.addListeners(TrainingListener... listeners) This method ADDS additional TrainingListener to existing listeners
void	VariationalAutoencoder.setListeners(TrainingListener... listeners)

Method parameters in org.deeplearning4j.nn.layers.variational with type arguments of type TrainingListener

Modifier and Type	Method and Description
void	VariationalAutoencoder.setListeners(Collection<TrainingListener> listeners)

Uses of TrainingListener in org.deeplearning4j.nn.layers.wrapper

Methods in org.deeplearning4j.nn.layers.wrapper that return types with arguments of type TrainingListener

Modifier and Type	Method and Description
Collection<TrainingListener>	BaseWrapperLayer.getListeners()

Methods in org.deeplearning4j.nn.layers.wrapper with parameters of type TrainingListener

Modifier and Type	Method and Description
void	BaseWrapperLayer.addListeners(TrainingListener... listener)
void	BaseWrapperLayer.setListeners(TrainingListener... listeners)

Method parameters in org.deeplearning4j.nn.layers.wrapper with type arguments of type TrainingListener

Modifier and Type	Method and Description
void	BaseWrapperLayer.setListeners(Collection<TrainingListener> listeners)

Uses of TrainingListener in org.deeplearning4j.nn.multilayer

Fields in org.deeplearning4j.nn.multilayer with type parameters of type TrainingListener

Modifier and Type	Field and Description
protected Collection<TrainingListener>	MultiLayerNetwork.trainingListeners

Methods in org.deeplearning4j.nn.multilayer that return types with arguments of type TrainingListener

Modifier and Type	Method and Description
Collection<TrainingListener>	MultiLayerNetwork.getListeners() Get the TrainingListeners set for this network, if any
Collection<TrainingListener>	MultiLayerNetwork.getTrainingListeners() Deprecated. Use MultiLayerNetwork.getListeners()

Methods in org.deeplearning4j.nn.multilayer with parameters of type TrainingListener

Modifier and Type	Method and Description
void	MultiLayerNetwork.addListeners(TrainingListener... listeners) This method ADDS additional TrainingListener to existing listeners
void	MultiLayerNetwork.setListeners(TrainingListener... listeners)

Method parameters in org.deeplearning4j.nn.multilayer with type arguments of type TrainingListener

Modifier and Type	Method and Description
void	MultiLayerNetwork.setListeners(Collection<TrainingListener> listeners)

Uses of TrainingListener in org.deeplearning4j.optimize

Methods in org.deeplearning4j.optimize with parameters of type TrainingListener

Modifier and Type	Method and Description
Solver.Builder	Solver.Builder.listener(TrainingListener... listeners)

Method parameters in org.deeplearning4j.optimize with type arguments of type TrainingListener

Modifier and Type	Method and Description
Solver.Builder	Solver.Builder.listeners(Collection<TrainingListener> listeners)
void	Solver.setListeners(Collection<TrainingListener> listeners)

Uses of TrainingListener in org.deeplearning4j.optimize.api

Classes in org.deeplearning4j.optimize.api that implement TrainingListener

Modifier and Type	Class and Description
class	BaseTrainingListener A no-op implementation of a TrainingListener to be used as a starting point for custom training callbacks.
class	IterationListener Deprecated. Use TrainingListener instead

Method parameters in org.deeplearning4j.optimize.api with type arguments of type TrainingListener

Modifier and Type	Method and Description
void	ConvexOptimizer.setListeners(Collection<TrainingListener> listeners)

Uses of TrainingListener in org.deeplearning4j.optimize.listeners

Classes in org.deeplearning4j.optimize.listeners that implement TrainingListener

Modifier and Type	Class and Description
class	CheckpointListener CheckpointListener: The goal of this listener is to periodically save a copy of the model during training.. Model saving may be done: 1.
class	CollectScoresIterationListener CollectScoresIterationListener simply stores the model scores internally (along with the iteration) every 1 or N iterations (this is configurable).
class	CollectScoresListener A simple listener that collects scores to a list every N iterations.
class	ComposableIterationListener Deprecated. Not required - DL4J networks can use multiple listeners simultaneously
class	EvaluativeListener This TrainingListener implementation provides simple way for model evaluation during training.
class	FailureTestingListener WARNING: THIS LISTENER SHOULD ONLY BE USED FOR MANUAL TESTING PURPOSES It intentionally causes various types of failures according to some criteria, in order to test the response to it. This is useful for example in: (a) Testing Spark fault tolerance (b) Testing OOM exception crash dump information Generally it should not be used in unit tests either, depending on how it is configured. Two aspects need to be configured to use this listener: 1.
class	PerformanceListener Simple IterationListener that tracks time spend on training per iteration.
class	ScoreIterationListener Score iteration listener.
class	SleepyTrainingListener This TrainingListener implementation provides a way to "sleep" during specific Neural Network training phases. Suitable for debugging/testing purposes only.
class	TimeIterationListener Time Iteration Listener.

Constructors in org.deeplearning4j.optimize.listeners with parameters of type TrainingListener

Constructor and Description
ComposableIterationListener(TrainingListener... TrainingListener) Deprecated.

Constructor parameters in org.deeplearning4j.optimize.listeners with type arguments of type TrainingListener

Constructor and Description
ComposableIterationListener(Collection<TrainingListener> listeners) Deprecated.

Uses of TrainingListener in org.deeplearning4j.optimize.solvers

Fields in org.deeplearning4j.optimize.solvers with type parameters of type TrainingListener

Modifier and Type	Field and Description
protected Collection<TrainingListener>	BaseOptimizer.trainingListeners

Method parameters in org.deeplearning4j.optimize.solvers with type arguments of type TrainingListener

Modifier and Type	Method and Description
void	BaseOptimizer.setListeners(Collection<TrainingListener> listeners)

Constructor parameters in org.deeplearning4j.optimize.solvers with type arguments of type TrainingListener

Constructor and Description
BaseOptimizer(NeuralNetConfiguration conf, StepFunction stepFunction, Collection<TrainingListener> trainingListeners, Model model)
ConjugateGradient(NeuralNetConfiguration conf, StepFunction stepFunction, Collection<TrainingListener> trainingListeners, Model model)
LBFGS(NeuralNetConfiguration conf, StepFunction stepFunction, Collection<TrainingListener> trainingListeners, Model model)
LineGradientDescent(NeuralNetConfiguration conf, StepFunction stepFunction, Collection<TrainingListener> trainingListeners, Model model)
StochasticGradientDescent(NeuralNetConfiguration conf, StepFunction stepFunction, Collection<TrainingListener> trainingListeners, Model model)