Uses of Class
org.deeplearning4j.nn.conf.layers.Layer

Packages that use Layer

Package	Description
org.deeplearning4j.nn.api
org.deeplearning4j.nn.conf
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.layers.wrapper
org.deeplearning4j.nn.conf.ocnn
org.deeplearning4j.nn.conf.serde
org.deeplearning4j.nn.layers
org.deeplearning4j.nn.layers.ocnn
org.deeplearning4j.nn.layers.util
org.deeplearning4j.nn.params
org.deeplearning4j.nn.transferlearning
org.deeplearning4j.util

Uses of Layer in org.deeplearning4j.nn.api

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

Modifier and Type	Method	Description
List<String>	ParamInitializer.biasKeys(Layer layer)	Bias parameter keys given the layer configuration
boolean	ParamInitializer.isBiasParam(Layer layer, String key)	Is the specified parameter a bias?
boolean	ParamInitializer.isWeightParam(Layer layer, String key)	Is the specified parameter a weight?
long	ParamInitializer.numParams(Layer layer)
List<String>	ParamInitializer.paramKeys(Layer layer)	Get a list of all parameter keys given the layer configuration
List<String>	ParamInitializer.weightKeys(Layer layer)	Weight parameter keys given the layer configuration

Uses of Layer in org.deeplearning4j.nn.conf

Fields in org.deeplearning4j.nn.conf declared as Layer

Modifier and Type	Field	Description
protected Layer	NeuralNetConfiguration.Builder.layer
protected Layer	NeuralNetConfiguration.layer

Methods in org.deeplearning4j.nn.conf with parameters of type Layer

Modifier and Type	Method	Description
ComputationGraphConfiguration.GraphBuilder	ComputationGraphConfiguration.GraphBuilder.addLayer(String layerName, Layer layer, String... layerInputs)	Add a layer, with no InputPreProcessor, with the specified name and specified inputs.
ComputationGraphConfiguration.GraphBuilder	ComputationGraphConfiguration.GraphBuilder.addLayer(String layerName, Layer layer, InputPreProcessor preProcessor, String... layerInputs)	Add a layer and an InputPreProcessor, with the specified name and specified inputs.
ComputationGraphConfiguration.GraphBuilder	ComputationGraphConfiguration.GraphBuilder.appendLayer(String layerName, Layer layer)	Add a layer, with no InputPreProcessor, with the specified name and input from the last added layer/vertex.
ComputationGraphConfiguration.GraphBuilder	ComputationGraphConfiguration.GraphBuilder.appendLayer(String layerName, Layer layer, InputPreProcessor preProcessor)	Add a layer and an InputPreProcessor, with the specified name and input from the last added layer/vertex.
ComputationGraphConfiguration.GraphBuilder	ComputationGraphConfiguration.GraphBuilder.layer(int layerName, Layer layer, String... layerInputs)	Add a layer, with no InputPreProcessor, with the specified name and specified inputs.
ComputationGraphConfiguration.GraphBuilder	ComputationGraphConfiguration.GraphBuilder.layer(String layerName, Layer layer, String... layerInputs)	Add a layer, with no InputPreProcessor, with the specified name and specified inputs.
ComputationGraphConfiguration.GraphBuilder	ComputationGraphConfiguration.GraphBuilder.layer(String layerName, Layer layer, InputPreProcessor preProcessor, String... layerInputs)	Add a layer and an InputPreProcessor, with the specified name and specified inputs.
NeuralNetConfiguration.Builder	NeuralNetConfiguration.Builder.layer(Layer layer)	Layer class.
NeuralNetConfiguration.ListBuilder	NeuralNetConfiguration.ListBuilder.layer(int ind, @NonNull Layer layer)
NeuralNetConfiguration.ListBuilder	NeuralNetConfiguration.ListBuilder.layer(Layer layer)
NeuralNetConfiguration.ListBuilder	NeuralNetConfiguration.Builder.list(Layer... layers)	Create a ListBuilder (for creating a MultiLayerConfiguration) with the specified layers Usage:

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

Subclasses of Layer in org.deeplearning4j.nn.conf.layers

Modifier and Type	Class	Description
class	AbstractLSTM
class	ActivationLayer
class	AutoEncoder
class	BaseLayer	A neural network layer.
class	BaseOutputLayer
class	BasePretrainNetwork
class	BaseRecurrentLayer
class	BaseUpsamplingLayer	Upsampling base layer
class	BatchNormalization
class	CapsuleLayer
class	CapsuleStrengthLayer
class	CenterLossOutputLayer
class	Cnn3DLossLayer
class	CnnLossLayer
class	Convolution1D
class	Convolution1DLayer
class	Convolution2D
class	Convolution3D
class	ConvolutionLayer
class	Deconvolution2D
class	Deconvolution3D
class	DenseLayer
class	DepthwiseConvolution2D
class	DropoutLayer
class	EmbeddingLayer
class	EmbeddingSequenceLayer
class	FeedForwardLayer
class	GlobalPoolingLayer
class	GravesBidirectionalLSTM	Deprecated.
class	GravesLSTM	Deprecated.
class	LearnedSelfAttentionLayer
class	LocallyConnected1D
class	LocallyConnected2D
class	LocalResponseNormalization
class	LossLayer
class	LSTM
class	NoParamLayer
class	OutputLayer
class	Pooling1D	1D Pooling (subsampling) layer.
class	Pooling2D	2D Pooling (subsampling) layer.
class	PReLULayer
class	PrimaryCapsules
class	RecurrentAttentionLayer
class	RnnLossLayer
class	RnnOutputLayer
class	SelfAttentionLayer
class	SeparableConvolution2D
class	SpaceToBatchLayer
class	SpaceToDepthLayer
class	Subsampling1DLayer
class	Subsampling3DLayer
class	SubsamplingLayer
class	Upsampling1D
class	Upsampling2D
class	Upsampling3D
class	ZeroPadding1DLayer
class	ZeroPadding3DLayer
class	ZeroPaddingLayer

Methods in org.deeplearning4j.nn.conf.layers with type parameters of type Layer

Modifier and Type	Method	Description
<E extends Layer> E	CapsuleLayer.Builder.build()
<E extends Layer> E	CapsuleStrengthLayer.Builder.build()
abstract <E extends Layer> E	Layer.Builder.build()
<E extends Layer> E	PrimaryCapsules.Builder.build()

Methods in org.deeplearning4j.nn.conf.layers that return Layer

Modifier and Type	Method	Description
Layer	Layer.clone()

Methods in org.deeplearning4j.nn.conf.layers with parameters of type Layer

Modifier and Type	Method	Description
static void	LayerValidation.generalValidation(String layerName, Layer layer, IDropout iDropout, List<Regularization> regularization, List<Regularization> regularizationBias, List<LayerConstraint> allParamConstraints, List<LayerConstraint> weightConstraints, List<LayerConstraint> biasConstraints)

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

Subclasses of Layer in org.deeplearning4j.nn.conf.layers.convolutional

Modifier and Type	Class	Description
class	Cropping1D
class	Cropping2D
class	Cropping3D

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

Subclasses of Layer in org.deeplearning4j.nn.conf.layers.misc

Modifier and Type	Class	Description
class	ElementWiseMultiplicationLayer
class	FrozenLayer
class	FrozenLayerWithBackprop	Frozen layer freezes parameters of the layer it wraps, but allows the backpropagation to continue.
class	RepeatVector

Fields in org.deeplearning4j.nn.conf.layers.misc declared as Layer

Modifier and Type	Field	Description
protected Layer	FrozenLayer.layer

Methods in org.deeplearning4j.nn.conf.layers.misc that return Layer

Modifier and Type	Method	Description
Layer	FrozenLayer.clone()
Layer	FrozenLayerWithBackprop.clone()

Methods in org.deeplearning4j.nn.conf.layers.misc with parameters of type Layer

Modifier and Type	Method	Description
FrozenLayer.Builder	FrozenLayer.Builder.layer(Layer layer)

Constructors in org.deeplearning4j.nn.conf.layers.misc with parameters of type Layer

Constructor	Description
FrozenLayer(Layer layer)
FrozenLayerWithBackprop(Layer layer)

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

Subclasses of Layer in org.deeplearning4j.nn.conf.layers.objdetect

Modifier and Type	Class	Description
class	Yolo2OutputLayer

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

Subclasses of Layer in org.deeplearning4j.nn.conf.layers.recurrent

Modifier and Type	Class	Description
class	Bidirectional
class	LastTimeStep
class	SimpleRnn
class	TimeDistributed

Methods in org.deeplearning4j.nn.conf.layers.recurrent that return Layer

Modifier and Type	Method	Description
Layer	LastTimeStep.getUnderlying()

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

Modifier and Type	Method	Description
Bidirectional.Builder	Bidirectional.Builder.rnnLayer(Layer layer)
void	Bidirectional.Builder.setLayer(Layer layer)

Constructors in org.deeplearning4j.nn.conf.layers.recurrent with parameters of type Layer

Constructor	Description
Bidirectional(@NonNull Layer layer)	Create a Bidirectional wrapper, with the default Mode (CONCAT) for the specified layer
Bidirectional(@NonNull Bidirectional.Mode mode, @NonNull Layer layer)	Create a Bidirectional wrapper for the specified layer
LastTimeStep(Layer underlying)
TimeDistributed(@NonNull Layer underlying, RNNFormat rnnDataFormat)
TimeDistributed(Layer underlying)

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

Subclasses of Layer in org.deeplearning4j.nn.conf.layers.samediff

Modifier and Type	Class	Description
class	AbstractSameDiffLayer
class	SameDiffLambdaLayer
class	SameDiffLayer
class	SameDiffOutputLayer

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

Subclasses of Layer in org.deeplearning4j.nn.conf.layers.util

Modifier and Type	Class	Description
class	MaskLayer
class	MaskZeroLayer

Methods in org.deeplearning4j.nn.conf.layers.util with parameters of type Layer

Modifier and Type	Method	Description
MaskZeroLayer.Builder	MaskZeroLayer.Builder.setUnderlying(Layer underlying)
MaskZeroLayer.Builder	MaskZeroLayer.Builder.underlying(Layer underlying)

Constructors in org.deeplearning4j.nn.conf.layers.util with parameters of type Layer

Constructor	Description
MaskZeroLayer(Layer underlying, double maskingValue)

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

Subclasses of Layer in org.deeplearning4j.nn.conf.layers.variational

Modifier and Type	Class	Description
class	VariationalAutoencoder

Uses of Layer in org.deeplearning4j.nn.conf.layers.wrapper

Subclasses of Layer in org.deeplearning4j.nn.conf.layers.wrapper

Modifier and Type	Class	Description
class	BaseWrapperLayer

Fields in org.deeplearning4j.nn.conf.layers.wrapper declared as Layer

Modifier and Type	Field	Description
protected Layer	BaseWrapperLayer.underlying

Constructors in org.deeplearning4j.nn.conf.layers.wrapper with parameters of type Layer

Constructor	Description
BaseWrapperLayer(Layer underlying)

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

Subclasses of Layer in org.deeplearning4j.nn.conf.ocnn

Modifier and Type	Class	Description
class	OCNNOutputLayer

Uses of Layer in org.deeplearning4j.nn.conf.serde

Methods in org.deeplearning4j.nn.conf.serde with parameters of type Layer

Modifier and Type	Method	Description
protected boolean	BaseNetConfigDeserializer.requiresActivationFromLegacy(Layer[] layers)
protected boolean	BaseNetConfigDeserializer.requiresDropoutFromLegacy(Layer[] layers)
protected boolean	BaseNetConfigDeserializer.requiresIUpdaterFromLegacy(Layer[] layers)
protected boolean	BaseNetConfigDeserializer.requiresLegacyLossHandling(Layer[] layers)
protected boolean	BaseNetConfigDeserializer.requiresRegularizationFromLegacy(Layer[] layers)
protected boolean	BaseNetConfigDeserializer.requiresWeightInitFromLegacy(Layer[] layers)

Uses of Layer in org.deeplearning4j.nn.layers

Classes in org.deeplearning4j.nn.layers with type parameters of type Layer

Modifier and Type	Class	Description
class	AbstractLayer<LayerConfT extends Layer>	A layer with input and output, no parameters or gradients

Uses of Layer in org.deeplearning4j.nn.layers.ocnn

Methods in org.deeplearning4j.nn.layers.ocnn with parameters of type Layer

Modifier and Type	Method	Description
List<String>	OCNNParamInitializer.biasKeys(Layer layer)
boolean	OCNNParamInitializer.isBiasParam(Layer layer, String key)
boolean	OCNNParamInitializer.isWeightParam(Layer layer, String key)
long	OCNNParamInitializer.numParams(Layer layer)
List<String>	OCNNParamInitializer.paramKeys(Layer layer)
List<String>	OCNNParamInitializer.weightKeys(Layer layer)

Uses of Layer in org.deeplearning4j.nn.layers.util

Subclasses of Layer in org.deeplearning4j.nn.layers.util

Modifier and Type	Class	Description
class	IdentityLayer

Uses of Layer in org.deeplearning4j.nn.params

Methods in org.deeplearning4j.nn.params with parameters of type Layer

Modifier and Type	Method	Description
List<String>	BatchNormalizationParamInitializer.biasKeys(Layer layer)
List<String>	BidirectionalParamInitializer.biasKeys(Layer layer)
List<String>	ConvolutionParamInitializer.biasKeys(Layer layer)
List<String>	DefaultParamInitializer.biasKeys(Layer layer)
List<String>	DepthwiseConvolutionParamInitializer.biasKeys(Layer layer)
List<String>	EmptyParamInitializer.biasKeys(Layer layer)
List<String>	FrozenLayerParamInitializer.biasKeys(Layer layer)
List<String>	FrozenLayerWithBackpropParamInitializer.biasKeys(Layer layer)
List<String>	GravesBidirectionalLSTMParamInitializer.biasKeys(Layer layer)
List<String>	GravesLSTMParamInitializer.biasKeys(Layer layer)
List<String>	LSTMParamInitializer.biasKeys(Layer layer)
List<String>	PReLUParamInitializer.biasKeys(Layer layer)
List<String>	SameDiffParamInitializer.biasKeys(Layer layer)
List<String>	SeparableConvolutionParamInitializer.biasKeys(Layer layer)
List<String>	SimpleRnnParamInitializer.biasKeys(Layer layer)
List<String>	VariationalAutoencoderParamInitializer.biasKeys(Layer layer)
List<String>	WrapperLayerParamInitializer.biasKeys(Layer layer)
protected boolean	DefaultParamInitializer.hasBias(Layer layer)
protected boolean	DefaultParamInitializer.hasLayerNorm(Layer layer)
protected boolean	SimpleRnnParamInitializer.hasLayerNorm(Layer layer)
boolean	BatchNormalizationParamInitializer.isBiasParam(Layer layer, String key)
boolean	BidirectionalParamInitializer.isBiasParam(Layer layer, String key)
boolean	ConvolutionParamInitializer.isBiasParam(Layer layer, String key)
boolean	DefaultParamInitializer.isBiasParam(Layer layer, String key)
boolean	DepthwiseConvolutionParamInitializer.isBiasParam(Layer layer, String key)
boolean	EmptyParamInitializer.isBiasParam(Layer layer, String key)
boolean	FrozenLayerParamInitializer.isBiasParam(Layer layer, String key)
boolean	FrozenLayerWithBackpropParamInitializer.isBiasParam(Layer layer, String key)
boolean	GravesBidirectionalLSTMParamInitializer.isBiasParam(Layer layer, String key)
boolean	GravesLSTMParamInitializer.isBiasParam(Layer layer, String key)
boolean	LSTMParamInitializer.isBiasParam(Layer layer, String key)
boolean	PReLUParamInitializer.isBiasParam(Layer layer, String key)
boolean	SameDiffParamInitializer.isBiasParam(Layer layer, String key)
boolean	SeparableConvolutionParamInitializer.isBiasParam(Layer layer, String key)
boolean	SimpleRnnParamInitializer.isBiasParam(Layer layer, String key)
boolean	VariationalAutoencoderParamInitializer.isBiasParam(Layer layer, String key)
boolean	WrapperLayerParamInitializer.isBiasParam(Layer layer, String key)
boolean	BatchNormalizationParamInitializer.isWeightParam(Layer layer, String key)
boolean	BidirectionalParamInitializer.isWeightParam(Layer layer, String key)
boolean	ConvolutionParamInitializer.isWeightParam(Layer layer, String key)
boolean	DefaultParamInitializer.isWeightParam(Layer layer, String key)
boolean	DepthwiseConvolutionParamInitializer.isWeightParam(Layer layer, String key)
boolean	EmptyParamInitializer.isWeightParam(Layer layer, String key)
boolean	FrozenLayerParamInitializer.isWeightParam(Layer layer, String key)
boolean	FrozenLayerWithBackpropParamInitializer.isWeightParam(Layer layer, String key)
boolean	GravesBidirectionalLSTMParamInitializer.isWeightParam(Layer layer, String key)
boolean	GravesLSTMParamInitializer.isWeightParam(Layer layer, String key)
boolean	LSTMParamInitializer.isWeightParam(Layer layer, String key)
boolean	PReLUParamInitializer.isWeightParam(Layer layer, String key)
boolean	SameDiffParamInitializer.isWeightParam(Layer layer, String key)
boolean	SeparableConvolutionParamInitializer.isWeightParam(Layer layer, String key)
boolean	SimpleRnnParamInitializer.isWeightParam(Layer layer, String key)
boolean	VariationalAutoencoderParamInitializer.isWeightParam(Layer layer, String key)
boolean	WrapperLayerParamInitializer.isWeightParam(Layer layer, String key)
long	BatchNormalizationParamInitializer.numParams(Layer l)
long	BidirectionalParamInitializer.numParams(Layer layer)
long	Convolution3DParamInitializer.numParams(Layer l)
long	ConvolutionParamInitializer.numParams(Layer l)
long	Deconvolution3DParamInitializer.numParams(Layer l)
long	DefaultParamInitializer.numParams(Layer l)
long	DepthwiseConvolutionParamInitializer.numParams(Layer l)
long	ElementWiseParamInitializer.numParams(Layer layer)
long	EmptyParamInitializer.numParams(Layer layer)
long	FrozenLayerParamInitializer.numParams(Layer layer)
long	FrozenLayerWithBackpropParamInitializer.numParams(Layer layer)
long	GravesBidirectionalLSTMParamInitializer.numParams(Layer l)
long	GravesLSTMParamInitializer.numParams(Layer l)
long	LSTMParamInitializer.numParams(Layer l)
long	PReLUParamInitializer.numParams(Layer l)
long	SameDiffParamInitializer.numParams(Layer layer)
long	SeparableConvolutionParamInitializer.numParams(Layer l)
long	SimpleRnnParamInitializer.numParams(Layer layer)
long	WrapperLayerParamInitializer.numParams(Layer layer)
List<String>	BatchNormalizationParamInitializer.paramKeys(Layer layer)
List<String>	BidirectionalParamInitializer.paramKeys(Layer layer)
List<String>	ConvolutionParamInitializer.paramKeys(Layer layer)
List<String>	DefaultParamInitializer.paramKeys(Layer layer)
List<String>	DepthwiseConvolutionParamInitializer.paramKeys(Layer layer)
List<String>	EmptyParamInitializer.paramKeys(Layer layer)
List<String>	FrozenLayerParamInitializer.paramKeys(Layer layer)
List<String>	FrozenLayerWithBackpropParamInitializer.paramKeys(Layer layer)
List<String>	GravesBidirectionalLSTMParamInitializer.paramKeys(Layer layer)
List<String>	GravesLSTMParamInitializer.paramKeys(Layer layer)
List<String>	LSTMParamInitializer.paramKeys(Layer layer)
List<String>	PReLUParamInitializer.paramKeys(Layer layer)
List<String>	SameDiffParamInitializer.paramKeys(Layer layer)
List<String>	SeparableConvolutionParamInitializer.paramKeys(Layer layer)
List<String>	SimpleRnnParamInitializer.paramKeys(Layer layer)
List<String>	VariationalAutoencoderParamInitializer.paramKeys(Layer l)
List<String>	WrapperLayerParamInitializer.paramKeys(Layer layer)
List<String>	BatchNormalizationParamInitializer.weightKeys(Layer layer)
List<String>	BidirectionalParamInitializer.weightKeys(Layer layer)
List<String>	ConvolutionParamInitializer.weightKeys(Layer layer)
List<String>	DefaultParamInitializer.weightKeys(Layer layer)
List<String>	DepthwiseConvolutionParamInitializer.weightKeys(Layer layer)
List<String>	EmptyParamInitializer.weightKeys(Layer layer)
List<String>	FrozenLayerParamInitializer.weightKeys(Layer layer)
List<String>	FrozenLayerWithBackpropParamInitializer.weightKeys(Layer layer)
List<String>	GravesBidirectionalLSTMParamInitializer.weightKeys(Layer layer)
List<String>	GravesLSTMParamInitializer.weightKeys(Layer layer)
List<String>	LSTMParamInitializer.weightKeys(Layer layer)
List<String>	PReLUParamInitializer.weightKeys(Layer layer)
List<String>	SameDiffParamInitializer.weightKeys(Layer layer)
List<String>	SeparableConvolutionParamInitializer.weightKeys(Layer layer)
List<String>	SimpleRnnParamInitializer.weightKeys(Layer layer)
List<String>	VariationalAutoencoderParamInitializer.weightKeys(Layer layer)
List<String>	WrapperLayerParamInitializer.weightKeys(Layer layer)

Uses of Layer in org.deeplearning4j.nn.transferlearning

Methods in org.deeplearning4j.nn.transferlearning with parameters of type Layer

Modifier and Type	Method	Description
TransferLearning.Builder	TransferLearning.Builder.addLayer(Layer layer)	Add layers to the net Required if layers are removed.
TransferLearning.GraphBuilder	TransferLearning.GraphBuilder.addLayer(String layerName, Layer layer, String... layerInputs)	Add a layer of the specified configuration to the computation graph
TransferLearning.GraphBuilder	TransferLearning.GraphBuilder.addLayer(String layerName, Layer layer, InputPreProcessor preProcessor, String... layerInputs)	Add a layer with a specified preprocessor

Uses of Layer in org.deeplearning4j.util

Methods in org.deeplearning4j.util with parameters of type Layer

Modifier and Type	Method	Description
static Convolution3D.DataFormat	Convolution3DUtils.getFormatForLayer(Layer inputLayer)	Returns the Convolution3D.DataFormat for the associated layer.
static CNN2DFormat	ConvolutionUtils.getFormatForLayer(Layer layer)	Get the format for a given layer.
static RNNFormat	TimeSeriesUtils.getFormatFromRnnLayer(Layer layer)	Get the RNNFormat from the RNN layer, accounting for the presence of wrapper layers like Bidirectional, LastTimeStep, etc
static RNNFormat	Convolution1DUtils.getRnnFormatFromLayer(Layer layer)	Get the RNNFormat for the given layer.
static boolean	Convolution1DUtils.hasRnnDataFormat(Layer layer)	Returns true if the given layer has an RNNFormat.
static boolean	Convolution3DUtils.layerHasConvolution3DLayout(Layer layer)	Returns true if any of the layers are 3d convolution, pooling, or upsampling layers including: Convolution3D, Deconvolution3D, Subsampling3DLayer, Upsampling3D
static boolean	ConvolutionUtils.layerHasConvolutionLayout(Layer layer)	Returns true if a layer has a CNN2DFormat property.
static void	OutputLayerUtil.validateOutputLayer(String layerName, Layer layer)	Validate the output layer (or loss layer) configuration, to detect invalid consfiugrations.
static void	OutputLayerUtil.validateOutputLayerForClassifierEvaluation(Layer outputLayer, Class<? extends IEvaluation> classifierEval)	Validates if the output layer configuration is valid for classifier evaluation.