Uses of Interface
org.deeplearning4j.nn.api.Layer

Packages that use Layer

Package	Description
org.deeplearning4j.gradientcheck
org.deeplearning4j.nn.api.layers
org.deeplearning4j.nn.conf.constraint
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.conf.weightnoise
org.deeplearning4j.nn.graph
org.deeplearning4j.nn.graph.vertex
org.deeplearning4j.nn.graph.vertex.impl
org.deeplearning4j.nn.graph.vertex.impl.rnn
org.deeplearning4j.nn.layers
org.deeplearning4j.nn.layers.convolution
org.deeplearning4j.nn.layers.convolution.subsampling
org.deeplearning4j.nn.layers.convolution.upsampling
org.deeplearning4j.nn.layers.feedforward
org.deeplearning4j.nn.layers.feedforward.autoencoder
org.deeplearning4j.nn.layers.feedforward.dense
org.deeplearning4j.nn.layers.feedforward.elementwise
org.deeplearning4j.nn.layers.feedforward.embedding
org.deeplearning4j.nn.layers.mkldnn
org.deeplearning4j.nn.layers.normalization
org.deeplearning4j.nn.layers.objdetect
org.deeplearning4j.nn.layers.ocnn
org.deeplearning4j.nn.layers.pooling
org.deeplearning4j.nn.layers.recurrent
org.deeplearning4j.nn.layers.samediff
org.deeplearning4j.nn.layers.training
org.deeplearning4j.nn.layers.util
org.deeplearning4j.nn.layers.variational
org.deeplearning4j.nn.layers.wrapper
org.deeplearning4j.nn.multilayer
org.deeplearning4j.nn.updater

Uses of Layer in org.deeplearning4j.gradientcheck

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

Modifier and Type	Method and Description
static boolean	GradientCheckUtil.checkGradientsPretrainLayer(Layer layer, double epsilon, double maxRelError, double minAbsoluteError, boolean print, boolean exitOnFirstError, INDArray input, int rngSeed) Check backprop gradients for a pretrain layer NOTE: gradient checking pretrain layers can be difficult...

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

Subinterfaces of Layer in org.deeplearning4j.nn.api.layers

Modifier and Type	Interface and Description
interface	IOutputLayer
interface	RecurrentLayer

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

Modifier and Type	Method and Description
void	LayerConstraint.applyConstraint(Layer layer, int iteration, int epoch) Apply a given constraint to a layer at each iteration in the provided epoch, after parameters have been updated.

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

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

Modifier and Type	Method and Description
void	BaseConstraint.applyConstraint(Layer layer, int iteration, int epoch)

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

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

Modifier and Type	Method and Description
Layer	ActivationLayer.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	BatchNormalization.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	Cnn3DLossLayer.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	Convolution1DLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Convolution3D.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> iterationListeners, 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	Deconvolution2D.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	DepthwiseConvolution2D.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	EmbeddingLayer.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	GlobalPoolingLayer.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	GravesLSTM.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType) Deprecated.
abstract Layer	Layer.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	LossLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	LSTM.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	PReLULayer.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	RnnOutputLayer.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)
Layer	SpaceToBatchLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, 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	Subsampling1DLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	Subsampling3DLayer.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	Upsampling1D.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	Upsampling3D.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	ZeroPadding3DLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> iterationListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
Layer	ZeroPaddingLayer.instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Modifier and Type	Method and Description
INDArray	DropConnect.getParameter(Layer layer, String paramKey, int iteration, int epoch, boolean train, LayerWorkspaceMgr workspaceMgr)
INDArray	IWeightNoise.getParameter(Layer layer, String paramKey, int iteration, int epoch, boolean train, LayerWorkspaceMgr workspaceMgr) Get the parameter, after applying weight noise
INDArray	WeightNoise.getParameter(Layer layer, String paramKey, int iteration, int epoch, boolean train, LayerWorkspaceMgr workspaceMgr)

Uses of Layer in org.deeplearning4j.nn.graph

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

Modifier and Type	Field and Description
protected Layer[]	ComputationGraph.layers A list of layers.

Methods in org.deeplearning4j.nn.graph that return Layer

Modifier and Type	Method and Description
Layer	ComputationGraph.getLayer(int idx) Get the layer by the number of that layer, in range 0 to getNumLayers()-1 NOTE: This is different from the internal GraphVertex index for the layer
Layer	ComputationGraph.getLayer(String name) Get a given layer by name.
Layer[]	ComputationGraph.getLayers() Get all layers in the ComputationGraph
Layer	ComputationGraph.getOutputLayer(int outputLayerIdx) Get the specified output layer, by index.

Uses of Layer in org.deeplearning4j.nn.graph.vertex

Methods in org.deeplearning4j.nn.graph.vertex that return Layer

Modifier and Type	Method and Description
Layer	BaseWrapperVertex.getLayer()
Layer	GraphVertex.getLayer() Get the Layer (if any).

Uses of Layer in org.deeplearning4j.nn.graph.vertex.impl

Methods in org.deeplearning4j.nn.graph.vertex.impl that return Layer

Modifier and Type	Method and Description
Layer	ElementWiseVertex.getLayer()
Layer	InputVertex.getLayer()
Layer	L2NormalizeVertex.getLayer()
Layer	L2Vertex.getLayer()
Layer	LayerVertex.getLayer()
Layer	MergeVertex.getLayer()
Layer	PoolHelperVertex.getLayer()
Layer	PreprocessorVertex.getLayer()
Layer	ReshapeVertex.getLayer()
Layer	ScaleVertex.getLayer()
Layer	ShiftVertex.getLayer()
Layer	StackVertex.getLayer()
Layer	SubsetVertex.getLayer()
Layer	UnstackVertex.getLayer()

Constructors in org.deeplearning4j.nn.graph.vertex.impl with parameters of type Layer

Constructor and Description
LayerVertex(ComputationGraph graph, String name, int vertexIndex, Layer layer, InputPreProcessor layerPreProcessor, boolean outputVertex, DataType dataType) Create a network input vertex:
LayerVertex(ComputationGraph graph, String name, int vertexIndex, VertexIndices[] inputVertices, VertexIndices[] outputVertices, Layer layer, InputPreProcessor layerPreProcessor, boolean outputVertex, DataType dataType)

Uses of Layer in org.deeplearning4j.nn.graph.vertex.impl.rnn

Methods in org.deeplearning4j.nn.graph.vertex.impl.rnn that return Layer

Modifier and Type	Method and Description
Layer	DuplicateToTimeSeriesVertex.getLayer()
Layer	LastTimeStepVertex.getLayer()
Layer	ReverseTimeSeriesVertex.getLayer()

Uses of Layer in org.deeplearning4j.nn.layers

Classes in org.deeplearning4j.nn.layers that implement Layer

Modifier and Type	Class and Description
class	AbstractLayer<LayerConfT extends Layer> A layer with input and output, no parameters or gradients
class	ActivationLayer
class	BaseLayer<LayerConfT extends BaseLayer> A layer with parameters
class	BaseOutputLayer<LayerConfT extends BaseOutputLayer>
class	BasePretrainNetwork<LayerConfT extends BasePretrainNetwork>
class	DropoutLayer
class	FrozenLayer
class	FrozenLayerWithBackprop
class	LossLayer
class	OutputLayer
class	RepeatVector

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

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

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

Constructor and Description
FrozenLayer(Layer insideLayer)
FrozenLayerWithBackprop(Layer insideLayer)

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

Classes in org.deeplearning4j.nn.layers.convolution that implement Layer

Modifier and Type	Class and Description
class	Cnn3DLossLayer
class	CnnLossLayer
class	Convolution1DLayer
class	Convolution3DLayer
class	ConvolutionLayer
class	Cropping1DLayer
class	Cropping2DLayer
class	Cropping3DLayer
class	Deconvolution2DLayer
class	Deconvolution3DLayer
class	DepthwiseConvolution2DLayer
class	SeparableConvolution2DLayer
class	SpaceToBatch
class	SpaceToDepth
class	ZeroPadding1DLayer
class	ZeroPadding3DLayer
class	ZeroPaddingLayer

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

Modifier and Type	Method and Description
Layer	Cropping1DLayer.clone()
Layer	Cropping2DLayer.clone()
Layer	Cropping3DLayer.clone()
Layer	ZeroPadding1DLayer.clone()
Layer	ZeroPadding3DLayer.clone()
Layer	ZeroPaddingLayer.clone()

Uses of Layer in org.deeplearning4j.nn.layers.convolution.subsampling

Classes in org.deeplearning4j.nn.layers.convolution.subsampling that implement Layer

Modifier and Type	Class and Description
class	Subsampling1DLayer
class	Subsampling3DLayer
class	SubsamplingLayer

Uses of Layer in org.deeplearning4j.nn.layers.convolution.upsampling

Classes in org.deeplearning4j.nn.layers.convolution.upsampling that implement Layer

Modifier and Type	Class and Description
class	Upsampling1D
class	Upsampling2D
class	Upsampling3D

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

Classes in org.deeplearning4j.nn.layers.feedforward that implement Layer

Modifier and Type	Class and Description
class	PReLU

Uses of Layer in org.deeplearning4j.nn.layers.feedforward.autoencoder

Classes in org.deeplearning4j.nn.layers.feedforward.autoencoder that implement Layer

Modifier and Type	Class and Description
class	AutoEncoder

Uses of Layer in org.deeplearning4j.nn.layers.feedforward.dense

Classes in org.deeplearning4j.nn.layers.feedforward.dense that implement Layer

Modifier and Type	Class and Description
class	DenseLayer

Uses of Layer in org.deeplearning4j.nn.layers.feedforward.elementwise

Classes in org.deeplearning4j.nn.layers.feedforward.elementwise that implement Layer

Modifier and Type	Class and Description
class	ElementWiseMultiplicationLayer

Uses of Layer in org.deeplearning4j.nn.layers.feedforward.embedding

Classes in org.deeplearning4j.nn.layers.feedforward.embedding that implement Layer

Modifier and Type	Class and Description
class	EmbeddingLayer
class	EmbeddingSequenceLayer

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

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

Modifier and Type

Method and Description

FwdPassReturn

MKLDNNLSTMHelper.activate(Layer layer, NeuralNetConfiguration conf, IActivation gateActivationFn, INDArray input, INDArray recurrentWeights, INDArray inputWeights, INDArray biases, boolean training, INDArray prevOutputActivations, INDArray prevMemCellState, boolean forBackprop, boolean forwards, String inputWeightKey, INDArray maskArray, boolean hasPeepholeConnections, LayerWorkspaceMgr workspaceMgr)

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

Classes in org.deeplearning4j.nn.layers.normalization that implement Layer

Modifier and Type	Class and Description
class	BatchNormalization
class	LocalResponseNormalization

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

Modifier and Type	Method and Description
Layer	LocalResponseNormalization.clone()

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

Classes in org.deeplearning4j.nn.layers.objdetect that implement Layer

Modifier and Type	Class and Description
class	Yolo2OutputLayer

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

Modifier and Type	Method and Description
Layer	Yolo2OutputLayer.clone()

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

Classes in org.deeplearning4j.nn.layers.ocnn that implement Layer

Modifier and Type	Class and Description
class	OCNNOutputLayer

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

Classes in org.deeplearning4j.nn.layers.pooling that implement Layer

Modifier and Type	Class and Description
class	GlobalPoolingLayer

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

Modifier and Type	Method and Description
Layer	GlobalPoolingLayer.clone()

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

Classes in org.deeplearning4j.nn.layers.recurrent that implement Layer

Modifier and Type	Class and Description
class	BaseRecurrentLayer<LayerConfT extends BaseRecurrentLayer>
class	BidirectionalLayer
class	GravesBidirectionalLSTM
class	GravesLSTM Deprecated.
class	LastTimeStepLayer
class	LSTM
class	MaskZeroLayer
class	RnnLossLayer
class	RnnOutputLayer
class	SimpleRnn
class	TimeDistributedLayer

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

Modifier and Type	Method and Description
FwdPassReturn	LSTMHelper.activate(Layer layer, NeuralNetConfiguration conf, IActivation gateActivationFn, INDArray input, INDArray recurrentWeights, INDArray inputWeights, INDArray biases, boolean training, INDArray prevOutputActivations, INDArray prevMemCellState, boolean forBackprop, boolean forwards, String inputWeightKey, INDArray maskArray, boolean hasPeepholeConnections, LayerWorkspaceMgr workspaceMgr)

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

Constructor and Description
BidirectionalLayer(@NonNull NeuralNetConfiguration conf, @NonNull Layer fwd, @NonNull Layer bwd, @NonNull INDArray paramsView)
BidirectionalLayer(@NonNull NeuralNetConfiguration conf, @NonNull Layer fwd, @NonNull Layer bwd, @NonNull INDArray paramsView)
LastTimeStepLayer(@NonNull Layer underlying)
MaskZeroLayer(@NonNull Layer underlying, double maskingValue)
TimeDistributedLayer(Layer underlying, RNNFormat rnnDataFormat)

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

Classes in org.deeplearning4j.nn.layers.samediff that implement Layer

Modifier and Type	Class and Description
class	SameDiffLayer
class	SameDiffOutputLayer

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

Modifier and Type	Method and Description
Layer	SameDiffLayer.clone()
Layer	SameDiffOutputLayer.clone()
Layer	SameDiffGraphVertex.getLayer()

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

Classes in org.deeplearning4j.nn.layers.training that implement Layer

Modifier and Type	Class and Description
class	CenterLossOutputLayer

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

Classes in org.deeplearning4j.nn.layers.util that implement Layer

Modifier and Type	Class and Description
class	MaskLayer

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

Modifier and Type	Method and Description
Layer	MaskLayer.clone()

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

Classes in org.deeplearning4j.nn.layers.variational that implement Layer

Modifier and Type	Class and Description
class	VariationalAutoencoder

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

Classes in org.deeplearning4j.nn.layers.wrapper that implement Layer

Modifier and Type	Class and Description
class	BaseWrapperLayer

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

Modifier and Type	Field and Description
protected Layer	BaseWrapperLayer.underlying

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

Constructor and Description
BaseWrapperLayer(@NonNull Layer underlying)

Uses of Layer in org.deeplearning4j.nn.multilayer

Classes in org.deeplearning4j.nn.multilayer that implement Layer

Modifier and Type	Class and Description
class	MultiLayerNetwork

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

Modifier and Type	Field and Description
protected Layer[]	MultiLayerNetwork.layers

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

Modifier and Type	Field and Description
protected LinkedHashMap<String,Layer>	MultiLayerNetwork.layerMap

Methods in org.deeplearning4j.nn.multilayer that return Layer

Modifier and Type	Method and Description
Layer	MultiLayerNetwork.getLayer(int i)
Layer	MultiLayerNetwork.getLayer(String name)
Layer[]	MultiLayerNetwork.getLayers()
Layer	MultiLayerNetwork.getOutputLayer() Get the output layer - i.e., the last layer in the netwok

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

Modifier and Type	Method and Description
void	MultiLayerNetwork.setLayers(Layer[] layers)

Uses of Layer in org.deeplearning4j.nn.updater

Constructors in org.deeplearning4j.nn.updater with parameters of type Layer

Constructor and Description
LayerUpdater(Layer layer)
LayerUpdater(Layer layer, INDArray updaterState)