Uses of Interface
org.deeplearning4j.nn.gradient.Gradient

Packages that use Gradient

Package	Description
org.deeplearning4j.nn.api
org.deeplearning4j.nn.api.layers
org.deeplearning4j.nn.gradient
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.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
org.deeplearning4j.optimize.api
org.deeplearning4j.optimize.solvers

Uses of Gradient in org.deeplearning4j.nn.api

Methods in org.deeplearning4j.nn.api that return Gradient

Modifier and Type	Method	Description
Gradient	Model.gradient()	Get the gradient.

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	Layer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)	Calculate the gradient relative to the error in the next layer
Pair<Gradient,Double>	Model.gradientAndScore()	Get the gradient and score

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

Modifier and Type	Method	Description
void	Model.update(Gradient gradient)	Update layer weights and biases with gradient change
void	Updater.update(Trainable layer, Gradient gradient, int iteration, int epoch, int miniBatchSize, LayerWorkspaceMgr workspaceMgr)	Updater: updates the model

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

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	RecurrentLayer.tbpttBackpropGradient(INDArray epsilon, int tbpttBackLength, LayerWorkspaceMgr workspaceMgr)	Truncated BPTT equivalent of Layer.backpropGradient().

Uses of Gradient in org.deeplearning4j.nn.gradient

Classes in org.deeplearning4j.nn.gradient that implement Gradient

Modifier and Type	Class	Description
class	DefaultGradient

Uses of Gradient in org.deeplearning4j.nn.graph

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

Modifier and Type	Field	Description
protected Gradient	ComputationGraph.gradient

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

Modifier and Type	Method	Description
Gradient	ComputationGraph.backpropGradient(INDArray... epsilons)	Calculate the gradient of the network with respect to some external errors.
Gradient	ComputationGraph.gradient()

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

Modifier and Type	Method	Description
Pair<Gradient,Double>	ComputationGraph.gradientAndScore()

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

Modifier and Type	Method	Description
void	ComputationGraph.update(Gradient gradient)

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

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray[]>	BaseWrapperVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	GraphVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)	Do backward pass

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

Methods in org.deeplearning4j.nn.graph.vertex.impl that return types with arguments of type Gradient

Modifier and Type	Method	Description
Pair<Gradient,INDArray[]>	ElementWiseVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	InputVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	L2NormalizeVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	L2Vertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	LayerVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	MergeVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	PoolHelperVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	PreprocessorVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	ReshapeVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	ScaleVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	ShiftVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	StackVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	SubsetVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	UnstackVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)

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

Methods in org.deeplearning4j.nn.graph.vertex.impl.rnn that return types with arguments of type Gradient

Modifier and Type	Method	Description
Pair<Gradient,INDArray[]>	DuplicateToTimeSeriesVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	LastTimeStepVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	ReverseTimeSeriesVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)

Uses of Gradient in org.deeplearning4j.nn.layers

Fields in org.deeplearning4j.nn.layers declared as Gradient

Modifier and Type	Field	Description
protected Gradient	BaseLayer.gradient

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

Modifier and Type	Method	Description
protected Gradient	BasePretrainNetwork.createGradient(INDArray wGradient, INDArray vBiasGradient, INDArray hBiasGradient)
Gradient	AbstractLayer.gradient()
Gradient	BaseLayer.gradient()
Gradient	BaseOutputLayer.gradient()	Gets the gradient from one training iteration
Gradient	FrozenLayer.gradient()
Gradient	LossLayer.gradient()	Gets the gradient from one training iteration
Gradient	RepeatVector.gradient()

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	ActivationLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	BaseLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	BaseOutputLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	BasePretrainNetwork.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	DropoutLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	FrozenLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	FrozenLayerWithBackprop.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	LossLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	RepeatVector.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,Double>	AbstractLayer.gradientAndScore()
Pair<Gradient,Double>	BaseOutputLayer.gradientAndScore()
Pair<Gradient,Double>	FrozenLayer.gradientAndScore()
Pair<Gradient,Double>	LossLayer.gradientAndScore()

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

Modifier and Type	Method	Description
void	AbstractLayer.update(Gradient gradient)
void	BaseLayer.update(Gradient gradient)
void	FrozenLayer.update(Gradient gradient)
void	FrozenLayerWithBackprop.update(Gradient gradient)

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

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

Modifier and Type	Method	Description
Gradient	SpaceToBatch.gradient()
Gradient	SpaceToDepth.gradient()

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	Cnn3DLossLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	CnnLossLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Convolution1DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Convolution3DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	ConvolutionHelper.backpropGradient(INDArray input, INDArray weights, INDArray bias, INDArray delta, int[] kernel, int[] strides, int[] pad, INDArray biasGradView, INDArray weightGradView, IActivation afn, ConvolutionLayer.AlgoMode mode, ConvolutionLayer.BwdFilterAlgo bwdFilterAlgo, ConvolutionLayer.BwdDataAlgo bwdDataAlgo, ConvolutionMode convolutionMode, int[] dilation, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	ConvolutionLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Cropping1DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Cropping2DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Cropping3DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Deconvolution2DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Deconvolution3DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	DepthwiseConvolution2DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	SeparableConvolution2DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	SpaceToBatch.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	SpaceToDepth.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	ZeroPadding1DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	ZeroPadding3DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	ZeroPaddingLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

Methods in org.deeplearning4j.nn.layers.convolution.subsampling that return Gradient

Modifier and Type	Method	Description
Gradient	Subsampling3DLayer.gradient()
Gradient	SubsamplingLayer.gradient()

Methods in org.deeplearning4j.nn.layers.convolution.subsampling that return types with arguments of type Gradient

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	Subsampling1DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Subsampling3DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	SubsamplingHelper.backpropGradient(INDArray input, INDArray epsilon, int[] kernel, int[] strides, int[] pad, PoolingType poolingType, ConvolutionMode convolutionMode, int[] dilation, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	SubsamplingLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

Methods in org.deeplearning4j.nn.layers.convolution.upsampling that return Gradient

Modifier and Type	Method	Description
Gradient	Upsampling2D.gradient()
Gradient	Upsampling3D.gradient()

Methods in org.deeplearning4j.nn.layers.convolution.upsampling that return types with arguments of type Gradient

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	Upsampling1D.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Upsampling2D.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Upsampling3D.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	PReLU.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

Methods in org.deeplearning4j.nn.layers.feedforward.elementwise that return types with arguments of type Gradient

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	ElementWiseMultiplicationLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

Methods in org.deeplearning4j.nn.layers.feedforward.embedding that return types with arguments of type Gradient

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	EmbeddingLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	EmbeddingSequenceLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	MKLDNNBatchNormHelper.backpropGradient(INDArray input, INDArray epsilon, long[] shape, INDArray gamma, INDArray beta, INDArray dGammaView, INDArray dBetaView, double eps, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	MKLDNNConvHelper.backpropGradient(INDArray input, INDArray weights, INDArray bias, INDArray delta, int[] kernel, int[] strides, int[] pad, INDArray biasGradView, INDArray weightGradView, IActivation afn, ConvolutionLayer.AlgoMode mode, ConvolutionLayer.BwdFilterAlgo bwdFilterAlgo, ConvolutionLayer.BwdDataAlgo bwdDataAlgo, ConvolutionMode convolutionMode, int[] dilation, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	MKLDNNLocalResponseNormalizationHelper.backpropGradient(INDArray input, INDArray epsilon, double k, double n, double alpha, double beta, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	MKLDNNSubsamplingHelper.backpropGradient(INDArray input, INDArray epsilon, int[] kernel, int[] strides, int[] pad, PoolingType poolingType, ConvolutionMode convolutionMode, int[] dilation, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr)

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

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

Modifier and Type	Method	Description
Gradient	BatchNormalization.gradient()

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	BatchNormalization.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	BatchNormalizationHelper.backpropGradient(INDArray input, INDArray epsilon, long[] shape, INDArray gamma, INDArray beta, INDArray dGammaView, INDArray dBetaView, double eps, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	LocalResponseNormalization.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	LocalResponseNormalizationHelper.backpropGradient(INDArray input, INDArray epsilon, double k, double n, double alpha, double beta, LayerWorkspaceMgr workspaceMgr)

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

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	Yolo2OutputLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,Double>	Yolo2OutputLayer.gradientAndScore()

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

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	OCNNOutputLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	GlobalPoolingLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

Methods in org.deeplearning4j.nn.layers.recurrent that return Gradient

Modifier and Type	Method	Description
Gradient	BidirectionalLayer.gradient()
Gradient	GravesBidirectionalLSTM.gradient()
Gradient	GravesLSTM.gradient()	Deprecated.
Gradient	LSTM.gradient()

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	BidirectionalLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	GravesBidirectionalLSTM.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	GravesLSTM.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)	Deprecated.
Pair<Gradient,INDArray>	LastTimeStepLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	LSTM.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	LSTMHelper.backpropGradient(NeuralNetConfiguration conf, IActivation gateActivationFn, INDArray input, INDArray recurrentWeights, INDArray inputWeights, INDArray epsilon, boolean truncatedBPTT, int tbpttBackwardLength, FwdPassReturn fwdPass, boolean forwards, String inputWeightKey, String recurrentWeightKey, String biasWeightKey, Map<String,INDArray> gradientViews, INDArray maskArray, boolean hasPeepholeConnections, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	MaskZeroLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	RnnLossLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	RnnOutputLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	SimpleRnn.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	TimeDistributedLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
static Pair<Gradient,INDArray>	LSTMHelpers.backpropGradientHelper(BaseRecurrentLayer layer, NeuralNetConfiguration conf, IActivation gateActivationFn, INDArray input, INDArray recurrentWeights, INDArray inputWeights, INDArray epsilon, boolean truncatedBPTT, int tbpttBackwardLength, FwdPassReturn fwdPass, boolean forwards, String inputWeightKey, String recurrentWeightKey, String biasWeightKey, Map<String,INDArray> gradientViews, INDArray maskArray, boolean hasPeepholeConnections, LSTMHelper helper, LayerWorkspaceMgr workspaceMgr, boolean isHelperAllowFallback)
Pair<Gradient,Double>	BidirectionalLayer.gradientAndScore()
Pair<Gradient,INDArray>	BidirectionalLayer.tbpttBackpropGradient(INDArray epsilon, int tbpttBackLength, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	GravesBidirectionalLSTM.tbpttBackpropGradient(INDArray epsilon, int tbpttBackwardLength, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	GravesLSTM.tbpttBackpropGradient(INDArray epsilon, int tbpttBackwardLength, LayerWorkspaceMgr workspaceMgr)	Deprecated.
Pair<Gradient,INDArray>	LSTM.tbpttBackpropGradient(INDArray epsilon, int tbpttBackwardLength, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	SimpleRnn.tbpttBackpropGradient(INDArray epsilon, int tbpttBackLength, LayerWorkspaceMgr workspaceMgr)

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

Modifier and Type	Method	Description
void	BidirectionalLayer.update(Gradient gradient)

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

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	SameDiffLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	SameDiffOutputLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	SameDiffGraphVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)

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

Methods in org.deeplearning4j.nn.layers.training that return Gradient

Modifier and Type	Method	Description
Gradient	CenterLossOutputLayer.gradient()	Gets the gradient from one training iteration

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	CenterLossOutputLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,Double>	CenterLossOutputLayer.gradientAndScore()

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

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	MaskLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

Fields in org.deeplearning4j.nn.layers.variational declared as Gradient

Modifier and Type	Field	Description
protected Gradient	VariationalAutoencoder.gradient

Methods in org.deeplearning4j.nn.layers.variational that return Gradient

Modifier and Type	Method	Description
Gradient	VariationalAutoencoder.gradient()

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	VariationalAutoencoder.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,Double>	VariationalAutoencoder.gradientAndScore()

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

Modifier and Type	Method	Description
void	VariationalAutoencoder.update(Gradient gradient)

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

Methods in org.deeplearning4j.nn.layers.wrapper that return Gradient

Modifier and Type	Method	Description
Gradient	BaseWrapperLayer.gradient()

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	BaseWrapperLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,Double>	BaseWrapperLayer.gradientAndScore()

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

Modifier and Type	Method	Description
void	BaseWrapperLayer.update(Gradient gradient)

Uses of Gradient in org.deeplearning4j.nn.multilayer

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

Modifier and Type	Field	Description
protected Gradient	MultiLayerNetwork.gradient

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

Modifier and Type	Method	Description
Gradient	MultiLayerNetwork.gradient()

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

Modifier and Type	Method	Description
Pair<Gradient,INDArray>	MultiLayerNetwork.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
protected Pair<Gradient,INDArray>	MultiLayerNetwork.calcBackpropGradients(INDArray epsilon, boolean withOutputLayer, boolean tbptt, boolean returnInputActGrad)	Calculate gradients and errors.
Pair<Gradient,INDArray>	MultiLayerNetwork.calculateGradients(@NonNull INDArray features, @NonNull INDArray label, INDArray fMask, INDArray labelMask)	Calculate parameter gradients and input activation gradients given the input and labels, and optionally mask arrays
Pair<Gradient,Double>	MultiLayerNetwork.gradientAndScore()

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

Modifier and Type	Method	Description
void	MultiLayerNetwork.update(Gradient gradient)

Uses of Gradient in org.deeplearning4j.nn.updater

Methods in org.deeplearning4j.nn.updater with parameters of type Gradient

Modifier and Type	Method	Description
protected void	BaseMultiLayerUpdater.divideByMinibatch(boolean isExternal, Gradient gradient, int batchSize)
void	BaseMultiLayerUpdater.preApply(Trainable layer, Gradient gradient, int iteration)	Pre-apply: Apply gradient normalization/clipping
void	BaseMultiLayerUpdater.update(Trainable layer, Gradient gradient, int iteration, int epoch, int batchSize, LayerWorkspaceMgr workspaceMgr)
void	BaseMultiLayerUpdater.update(Gradient gradient, int iteration, int epoch, int batchSize, LayerWorkspaceMgr workspaceMgr)	Update the gradient for the model.

Uses of Gradient in org.deeplearning4j.optimize.api

Methods in org.deeplearning4j.optimize.api that return types with arguments of type Gradient

Modifier and Type	Method	Description
Pair<Gradient,Double>	ConvexOptimizer.gradientAndScore(LayerWorkspaceMgr workspaceMgr)	The gradient and score for this optimizer

Methods in org.deeplearning4j.optimize.api with parameters of type Gradient

Modifier and Type	Method	Description
void	ConvexOptimizer.updateGradientAccordingToParams(Gradient gradient, Model model, int batchSize, LayerWorkspaceMgr workspaceMgr)	Update the gradient according to the configuration such as adagrad, momentum, and sparsity

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

Modifier and Type	Method	Description
void	ConvexOptimizer.setupSearchState(Pair<Gradient,Double> pair)	Based on the gradient and score setup a search state

Uses of Gradient in org.deeplearning4j.optimize.solvers

Methods in org.deeplearning4j.optimize.solvers that return types with arguments of type Gradient

Modifier and Type	Method	Description
Pair<Gradient,Double>	BaseOptimizer.gradientAndScore(LayerWorkspaceMgr workspaceMgr)

Methods in org.deeplearning4j.optimize.solvers with parameters of type Gradient

Modifier and Type	Method	Description
void	BaseOptimizer.updateGradientAccordingToParams(Gradient gradient, Model model, int batchSize, LayerWorkspaceMgr workspaceMgr)

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

Modifier and Type	Method	Description
void	BaseOptimizer.setupSearchState(Pair<Gradient,Double> pair)	Setup the initial search state
void	LBFGS.setupSearchState(Pair<Gradient,Double> pair)