Uses of Interface org.deeplearning4j.arbiter.optimize.api.ParameterSpace (deeplearning4j 1.0.0-beta6 API)

Packages that use ParameterSpace
Package	Description
org.deeplearning4j.arbiter
org.deeplearning4j.arbiter.adapter
org.deeplearning4j.arbiter.conf.dropout
org.deeplearning4j.arbiter.conf.updater
org.deeplearning4j.arbiter.conf.updater.schedule
org.deeplearning4j.arbiter.dropout
org.deeplearning4j.arbiter.layers
org.deeplearning4j.arbiter.layers.fixed
org.deeplearning4j.arbiter.optimize.api
org.deeplearning4j.arbiter.optimize.api.adapter
org.deeplearning4j.arbiter.optimize.generator
org.deeplearning4j.arbiter.optimize.parameter
org.deeplearning4j.arbiter.optimize.parameter.continuous
org.deeplearning4j.arbiter.optimize.parameter.discrete
org.deeplearning4j.arbiter.optimize.parameter.integer
org.deeplearning4j.arbiter.optimize.parameter.math
org.deeplearning4j.arbiter.util

Uses of ParameterSpace in org.deeplearning4j.arbiter

Classes in org.deeplearning4j.arbiter that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`BaseNetworkSpace<T>` This is an abstract ParameterSpace for both MultiLayerNetworks (MultiLayerSpace) and ComputationGraph (ComputationGraphSpace) Functionality here should match `NeuralNetConfiguration.Builder`
`class`	`ComputationGraphSpace` ComputationGraphSpace: Defines the space of valid hyperparameters for a ComputationGraph.
`class`	`MultiLayerSpace`

Fields in org.deeplearning4j.arbiter declared as ParameterSpace
Modifier and Type	Field and Description
`protected ParameterSpace<IActivation>`	BaseNetworkSpace.`activationFunction`
`protected ParameterSpace<List<LayerConstraint>>`	BaseNetworkSpace.`allParamConstraints`
`protected ParameterSpace<BackpropType>`	BaseNetworkSpace.`backpropType`
`protected ParameterSpace<List<LayerConstraint>>`	BaseNetworkSpace.`biasConstraints`
`protected ParameterSpace<Double>`	BaseNetworkSpace.`biasInit`
`protected ParameterSpace<IUpdater>`	BaseNetworkSpace.`biasUpdater`
`protected ParameterSpace<ConvolutionMode>`	BaseNetworkSpace.`convolutionMode`
`protected ParameterSpace<Distribution>`	BaseNetworkSpace.`dist`
`protected ParameterSpace<GradientNormalization>`	BaseNetworkSpace.`gradientNormalization`
`protected ParameterSpace<Double>`	BaseNetworkSpace.`gradientNormalizationThreshold`
`protected ParameterSpace<Map<Integer,InputPreProcessor>>`	MultiLayerSpace.`inputPreProcessors`
`protected ParameterSpace<Map<Integer,InputPreProcessor>>`	MultiLayerSpace.Builder.`inputPreProcessors`
`protected ParameterSpace<InputType>`	MultiLayerSpace.`inputType`
`protected ParameterSpace<InputType>`	MultiLayerSpace.Builder.`inputType`
`protected ParameterSpace<InputType[]>`	ComputationGraphSpace.`inputTypes`
`protected ParameterSpace<InputType[]>`	ComputationGraphSpace.Builder.`inputTypes`
`protected ParameterSpace<Double>`	BaseNetworkSpace.`l1`
`protected ParameterSpace<Double>`	BaseNetworkSpace.`l1Bias`
`protected ParameterSpace<Double>`	BaseNetworkSpace.`l2`
`protected ParameterSpace<Double>`	BaseNetworkSpace.`l2Bias`
`protected ParameterSpace<Integer>`	BaseNetworkSpace.`maxNumLineSearchIterations`
`protected ParameterSpace<Boolean>`	BaseNetworkSpace.`miniBatch`
`protected ParameterSpace<Boolean>`	BaseNetworkSpace.`minimize`
`protected ParameterSpace<Integer>`	BaseNetworkSpace.LayerConf.`numLayers`
`protected ParameterSpace<OptimizationAlgorithm>`	BaseNetworkSpace.`optimizationAlgo`
`protected ParameterSpace<StepFunction>`	BaseNetworkSpace.`stepFunction`
`protected ParameterSpace<Integer>`	BaseNetworkSpace.`tbpttBwdLength`
`protected ParameterSpace<Integer>`	BaseNetworkSpace.`tbpttFwdLength`
`protected ParameterSpace<IUpdater>`	BaseNetworkSpace.`updater`
`protected ParameterSpace<List<LayerConstraint>>`	BaseNetworkSpace.`weightConstraints`
`protected ParameterSpace<WeightInit>`	BaseNetworkSpace.`weightInit`
`protected ParameterSpace<IWeightNoise>`	BaseNetworkSpace.`weightNoise`

Methods in org.deeplearning4j.arbiter that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	MultiLayerSpace.`collectLeaves()`
`List<ParameterSpace>`	ComputationGraphSpace.`collectLeaves()`
`List<ParameterSpace>`	BaseNetworkSpace.`collectLeaves()`

Methods in org.deeplearning4j.arbiter with parameters of type ParameterSpace
Modifier and Type	Method and Description
`T`	BaseNetworkSpace.Builder.`activation(ParameterSpace<Activation> activationFunction)`
`T`	BaseNetworkSpace.Builder.`activationFn(ParameterSpace<IActivation> activationFunction)`
`MultiLayerSpace.Builder`	MultiLayerSpace.Builder.`addLayer(LayerSpace<? extends Layer> layerSpace, ParameterSpace<Integer> numLayersDistribution)`
`MultiLayerSpace.Builder`	MultiLayerSpace.Builder.`addLayer(LayerSpace<? extends Layer> layerSpace, ParameterSpace<Integer> numLayersDistribution, boolean duplicateConfig)` Deprecated.
`T`	BaseNetworkSpace.Builder.`backpropType(ParameterSpace<BackpropType> backpropType)`
`T`	BaseNetworkSpace.Builder.`biasInit(ParameterSpace<Double> biasInit)`
`T`	BaseNetworkSpace.Builder.`biasUpdater(ParameterSpace<IUpdater> biasUpdater)`
`T`	BaseNetworkSpace.Builder.`constrainAllParams(ParameterSpace<List<LayerConstraint>> constraints)`
`T`	BaseNetworkSpace.Builder.`constrainBias(ParameterSpace<List<LayerConstraint>> constraints)`
`T`	BaseNetworkSpace.Builder.`constrainWeights(ParameterSpace<List<LayerConstraint>> constraints)`
`T`	BaseNetworkSpace.Builder.`convolutionMode(ParameterSpace<ConvolutionMode> convolutionMode)`
`T`	BaseNetworkSpace.Builder.`dist(ParameterSpace<Distribution> dist)`
`T`	BaseNetworkSpace.Builder.`dropOut(ParameterSpace<Double> dropOut)`
`T`	BaseNetworkSpace.Builder.`gradientNormalization(ParameterSpace<GradientNormalization> gradientNormalization)`
`T`	BaseNetworkSpace.Builder.`gradientNormalizationThreshold(ParameterSpace<Double> gradientNormalizationThreshold)`
`T`	BaseNetworkSpace.Builder.`idropOut(ParameterSpace<IDropout> idropOut)`
`T`	BaseNetworkSpace.Builder.`l1(ParameterSpace<Double> l1)`
`T`	BaseNetworkSpace.Builder.`l1Bias(ParameterSpace<Double> l1Bias)`
`T`	BaseNetworkSpace.Builder.`l2(ParameterSpace<Double> l2)`
`T`	BaseNetworkSpace.Builder.`l2Bias(ParameterSpace<Double> l2Bias)`
`MultiLayerSpace.Builder`	MultiLayerSpace.Builder.`layer(LayerSpace<? extends Layer> layerSpace, ParameterSpace<Integer> numLayersDistribution)`
`T`	BaseNetworkSpace.Builder.`maxNumLineSearchIterations(ParameterSpace<Integer> maxNumLineSearchIterations)`
`T`	BaseNetworkSpace.Builder.`miniBatch(ParameterSpace<Boolean> miniBatch)`
`T`	BaseNetworkSpace.Builder.`minimize(ParameterSpace<Boolean> minimize)`
`T`	BaseNetworkSpace.Builder.`optimizationAlgo(ParameterSpace<OptimizationAlgorithm> parameterSpace)`
`MultiLayerSpace.Builder`	MultiLayerSpace.Builder.`setInputPreProcessors(ParameterSpace<Map<Integer,InputPreProcessor>> inputPreProcessors)`
`MultiLayerSpace.Builder`	MultiLayerSpace.Builder.`setInputType(ParameterSpace<InputType> inputType)`
`ComputationGraphSpace.Builder`	ComputationGraphSpace.Builder.`setInputTypes(ParameterSpace<InputType[]> inputTypes)`
`T`	BaseNetworkSpace.Builder.`stepFunction(ParameterSpace<StepFunction> stepFunction)`
`T`	BaseNetworkSpace.Builder.`tbpttBwdLength(ParameterSpace<Integer> tbpttBwdLength)`
`T`	BaseNetworkSpace.Builder.`tbpttFwdLength(ParameterSpace<Integer> tbpttFwdLength)`
`T`	BaseNetworkSpace.Builder.`updater(ParameterSpace<IUpdater> updater)`
`T`	BaseNetworkSpace.Builder.`weightInit(ParameterSpace<WeightInit> weightInit)`
`T`	BaseNetworkSpace.Builder.`weightNoise(ParameterSpace<IWeightNoise> weightNoise)`

Uses of ParameterSpace in org.deeplearning4j.arbiter.adapter

Classes in org.deeplearning4j.arbiter.adapter that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`ActivationParameterSpaceAdapter` A simple class to adapt a `Activation` parameter space to a `IActivation` parameter space
`class`	`LossFunctionParameterSpaceAdapter` A simple class to adapt a `LossFunctions.LossFunction` parameter space to a `ILossFunction` parameter space

Methods in org.deeplearning4j.arbiter.adapter that return ParameterSpace
Modifier and Type	Method and Description
`protected ParameterSpace<LossFunctions.LossFunction>`	LossFunctionParameterSpaceAdapter.`underlying()`
`protected ParameterSpace<Activation>`	ActivationParameterSpaceAdapter.`underlying()`

Constructors in org.deeplearning4j.arbiter.adapter with parameters of type ParameterSpace
Constructor and Description
`ActivationParameterSpaceAdapter(ParameterSpace<Activation> activation)`
`LossFunctionParameterSpaceAdapter(ParameterSpace<LossFunctions.LossFunction> lossFunction)`

Uses of ParameterSpace in org.deeplearning4j.arbiter.conf.dropout

Classes in org.deeplearning4j.arbiter.conf.dropout that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`DropoutSpace`

Methods in org.deeplearning4j.arbiter.conf.dropout that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	DropoutSpace.`collectLeaves()`

Uses of ParameterSpace in org.deeplearning4j.arbiter.conf.updater

Classes in org.deeplearning4j.arbiter.conf.updater that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`AdaGradSpace`
`class`	`AdaMaxSpace`
`class`	`AdamSpace`
`class`	`BaseUpdaterSpace`
`class`	`NadamSpace`
`class`	`NesterovsSpace`
`class`	`RmsPropSpace`
`class`	`SgdSpace`

Fields in org.deeplearning4j.arbiter.conf.updater declared as ParameterSpace
Modifier and Type	Field and Description
`protected ParameterSpace<Double>`	SgdSpace.`learningRate`
`protected ParameterSpace<Double>`	RmsPropSpace.`learningRate`
`protected ParameterSpace<Double>`	NesterovsSpace.`learningRate`
`protected ParameterSpace<ISchedule>`	SgdSpace.`learningRateSchedule`
`protected ParameterSpace<ISchedule>`	RmsPropSpace.`learningRateSchedule`
`protected ParameterSpace<ISchedule>`	NesterovsSpace.`learningRateSchedule`
`protected ParameterSpace<Double>`	NesterovsSpace.`momentum`
`protected ParameterSpace<ISchedule>`	NesterovsSpace.`momentumSchedule`

Methods in org.deeplearning4j.arbiter.conf.updater that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	BaseUpdaterSpace.`collectLeaves()`

Methods in org.deeplearning4j.arbiter.conf.updater with parameters of type ParameterSpace
Modifier and Type	Method and Description
`static NesterovsSpace`	NesterovsSpace.`withLR(ParameterSpace<Double> lr)`
`static NadamSpace`	NadamSpace.`withLR(ParameterSpace<Double> lr)`
`static AdamSpace`	AdamSpace.`withLR(ParameterSpace<Double> lr)`
`static AdaMaxSpace`	AdaMaxSpace.`withLR(ParameterSpace<Double> lr)`
`static AdaGradSpace`	AdaGradSpace.`withLR(ParameterSpace<Double> lr)`
`static NesterovsSpace`	NesterovsSpace.`withLR(ParameterSpace<Double> lr, double momentum)`
`static NesterovsSpace`	NesterovsSpace.`withLR(ParameterSpace<Double> lr, ParameterSpace<Double> momentum)`
`static NesterovsSpace`	NesterovsSpace.`withLR(ParameterSpace<Double> lr, ParameterSpace<Double> momentum)`
`static NesterovsSpace`	NesterovsSpace.`withLRSchedule(ParameterSpace<ISchedule> lrSchedule)`
`static NadamSpace`	NadamSpace.`withLRSchedule(ParameterSpace<ISchedule> lrSchedule)`
`static AdamSpace`	AdamSpace.`withLRSchedule(ParameterSpace<ISchedule> lrSchedule)`
`static AdaMaxSpace`	AdaMaxSpace.`withLRSchedule(ParameterSpace<ISchedule> lrSchedule)`
`static AdaGradSpace`	AdaGradSpace.`withLRSchedule(ParameterSpace<ISchedule> lrSchedule)`
`static NesterovsSpace`	NesterovsSpace.`withLRSchedule(ParameterSpace<ISchedule> lrSchedule, double momentum)`
`static NesterovsSpace`	NesterovsSpace.`withLRSchedule(ParameterSpace<ISchedule> lrSchedule, ParameterSpace<Double> momentum)`
`static NesterovsSpace`	NesterovsSpace.`withLRSchedule(ParameterSpace<ISchedule> lrSchedule, ParameterSpace<Double> momentum)`

Constructors in org.deeplearning4j.arbiter.conf.updater with parameters of type ParameterSpace
Constructor and Description
`AdaGradSpace(ParameterSpace<Double> learningRate)`
`AdaGradSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> lrSchedule)`
`AdaGradSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> lrSchedule)`
`AdaMaxSpace(ParameterSpace<Double> learningRate)`
`AdaMaxSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdaMaxSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdaMaxSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdaMaxSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdaMaxSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdaMaxSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdaMaxSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdaMaxSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdaMaxSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdamSpace(ParameterSpace<Double> learningRate)`
`AdamSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdamSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdamSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdamSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`AdamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NadamSpace(ParameterSpace<Double> learningRate)`
`NadamSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NadamSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NadamSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NadamSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NadamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NadamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NadamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NadamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NadamSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> beta1, ParameterSpace<Double> beta2, ParameterSpace<Double> epsilon)`
`NesterovsSpace(ParameterSpace<Double> learningRate)`
`NesterovsSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> momentum)`
`NesterovsSpace(ParameterSpace<Double> learningRate, ParameterSpace<Double> momentum)`
`NesterovsSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> momentum, ParameterSpace<ISchedule> momentumSchedule)`
`NesterovsSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> momentum, ParameterSpace<ISchedule> momentumSchedule)`
`NesterovsSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> momentum, ParameterSpace<ISchedule> momentumSchedule)`
`NesterovsSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule, ParameterSpace<Double> momentum, ParameterSpace<ISchedule> momentumSchedule)`
`RmsPropSpace(ParameterSpace<Double> learningRate)`
`RmsPropSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule)`
`RmsPropSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule)`
`SgdSpace(ParameterSpace<Double> learningRate)`
`SgdSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule)`
`SgdSpace(ParameterSpace<Double> learningRate, ParameterSpace<ISchedule> learningRateSchedule)`

Uses of ParameterSpace in org.deeplearning4j.arbiter.conf.updater.schedule

Classes in org.deeplearning4j.arbiter.conf.updater.schedule that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`ExponentialScheduleSpace`
`class`	`InverseScheduleSpace`
`class`	`PolyScheduleSpace`
`class`	`SigmoidScheduleSpace`
`class`	`StepScheduleSpace`

Methods in org.deeplearning4j.arbiter.conf.updater.schedule that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	StepScheduleSpace.`collectLeaves()`
`List<ParameterSpace>`	SigmoidScheduleSpace.`collectLeaves()`
`List<ParameterSpace>`	PolyScheduleSpace.`collectLeaves()`
`List<ParameterSpace>`	InverseScheduleSpace.`collectLeaves()`
`List<ParameterSpace>`	ExponentialScheduleSpace.`collectLeaves()`
`Map<String,ParameterSpace>`	StepScheduleSpace.`getNestedSpaces()`
`Map<String,ParameterSpace>`	SigmoidScheduleSpace.`getNestedSpaces()`
`Map<String,ParameterSpace>`	PolyScheduleSpace.`getNestedSpaces()`
`Map<String,ParameterSpace>`	InverseScheduleSpace.`getNestedSpaces()`
`Map<String,ParameterSpace>`	ExponentialScheduleSpace.`getNestedSpaces()`

Constructors in org.deeplearning4j.arbiter.conf.updater.schedule with parameters of type ParameterSpace
Constructor and Description
`ExponentialScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, double gamma)`
`ExponentialScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> gamma)`
`ExponentialScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> gamma)`
`InverseScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, double gamma, double power)`
`InverseScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> gamma, ParameterSpace<Double> power)`
`InverseScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> gamma, ParameterSpace<Double> power)`
`InverseScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> gamma, ParameterSpace<Double> power)`
`PolyScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, double power, int maxIter)`
`PolyScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> power, ParameterSpace<Integer> maxIter)`
`PolyScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> power, ParameterSpace<Integer> maxIter)`
`PolyScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> power, ParameterSpace<Integer> maxIter)`
`SigmoidScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, double gamma, int stepSize)`
`SigmoidScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> gamma, ParameterSpace<Integer> stepSize)`
`SigmoidScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> gamma, ParameterSpace<Integer> stepSize)`
`SigmoidScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> gamma, ParameterSpace<Integer> stepSize)`
`StepScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, double decayRate, double step)`
`StepScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> decayRate, ParameterSpace<Double> step)`
`StepScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> decayRate, ParameterSpace<Double> step)`
`StepScheduleSpace(ScheduleType scheduleType, ParameterSpace<Double> initialValue, ParameterSpace<Double> decayRate, ParameterSpace<Double> step)`

Uses of ParameterSpace in org.deeplearning4j.arbiter.dropout

Classes in org.deeplearning4j.arbiter.dropout that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`AlphaDropoutSpace`
`class`	`GaussianDropoutSpace`
`class`	`GaussianNoiseSpace`

Methods in org.deeplearning4j.arbiter.dropout that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	GaussianNoiseSpace.`collectLeaves()`
`List<ParameterSpace>`	GaussianDropoutSpace.`collectLeaves()`
`List<ParameterSpace>`	DropoutSpace.`collectLeaves()`
`List<ParameterSpace>`	AlphaDropoutSpace.`collectLeaves()`
`Map<String,ParameterSpace>`	GaussianNoiseSpace.`getNestedSpaces()`
`Map<String,ParameterSpace>`	GaussianDropoutSpace.`getNestedSpaces()`
`Map<String,ParameterSpace>`	DropoutSpace.`getNestedSpaces()`
`Map<String,ParameterSpace>`	AlphaDropoutSpace.`getNestedSpaces()`

Uses of ParameterSpace in org.deeplearning4j.arbiter.layers

Classes in org.deeplearning4j.arbiter.layers that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`AbstractLSTMLayerSpace<T extends AbstractLSTM>` Layer space for LSTM layers
`class`	`ActivationLayerSpace` Layer space for `ActivationLayer`
`class`	`AutoEncoderLayerSpace` Layer space for autoencoder layers
`class`	`BaseConvolutionLayerSpace<T extends FeedForwardLayer>` Layer space for convolutional layers
`class`	`BaseLayerSpace<L extends BaseLayer>` BaseLayerSpace contains the common Layer hyperparameters; should match `BaseLayer` in terms of features
`class`	`BaseOutputLayerSpace<L extends BaseOutputLayer>`
`class`	`BasePretrainNetworkLayerSpace<L extends BasePretrainNetwork>`
`class`	`BatchNormalizationSpace` LayerSpace for batch normalization layers
`class`	`Bidirectional` Bidirectional layer wrapper.
`class`	`CenterLossOutputLayerSpace`
`class`	`ConvolutionLayerSpace` Layer space for convolutional layers
`class`	`Deconvolution2DLayerSpace`
`class`	`DenseLayerSpace` layer hyperparameter configuration space for dense layers (i.e., multi-layer perceptron layers)
`class`	`DropoutLayerSpace`
`class`	`EmbeddingLayerSpace` Layer hyperparameter configuration space for `EmbeddingLayer`
`class`	`FeedForwardLayerSpace<L extends FeedForwardLayer>`
`class`	`GlobalPoolingLayerSpace` Layer space for a `GlobalPoolingLayer`
`class`	`GravesBidirectionalLSTMLayerSpace` Layer space for Bidirectional LSTM layers
`class`	`GravesLSTMLayerSpace` Layer space for LSTM layers
`class`	`LayerSpace<L extends Layer>` LayerSpace contains common Layer hyperparameters; should match `Layer` in terms of features
`class`	`LocalResponseNormalizationLayerSpace`
`class`	`LossLayerSpace`
`class`	`LSTMLayerSpace` Layer space for LSTM layers
`class`	`OCNNLayerSpace`
`class`	`OutputLayerSpace` Layer hyperparameter configuration space for output layers
`class`	`RnnOutputLayerSpace` Layer hyperparametor configuration space for RnnOutputLayer
`class`	`SeparableConvolution2DLayerSpace`
`class`	`SubsamplingLayerSpace` Layer hyperparameter configuration space for subsampling layers
`class`	`VariationalAutoencoderLayerSpace` Layer space for `VariationalAutoencoder`

Fields in org.deeplearning4j.arbiter.layers declared as ParameterSpace
Modifier and Type	Field and Description
`protected ParameterSpace<IActivation>`	BaseLayerSpace.`activationFunction`
`protected ParameterSpace<IActivation>`	BaseLayerSpace.Builder.`activationFunction`
`protected ParameterSpace<Double>`	BatchNormalizationSpace.`beta`
`protected ParameterSpace<Double>`	BatchNormalizationSpace.Builder.`beta`
`protected ParameterSpace<List<LayerConstraint>>`	BatchNormalizationSpace.Builder.`betaConstraints`
`protected ParameterSpace<Double>`	BaseLayerSpace.`biasInit`
`protected ParameterSpace<Double>`	BaseLayerSpace.Builder.`biasInit`
`protected ParameterSpace<IUpdater>`	BaseLayerSpace.`biasUpdater`
`protected ParameterSpace<IUpdater>`	BaseLayerSpace.Builder.`biasUpdater`
`protected ParameterSpace<Boolean>`	GlobalPoolingLayerSpace.`collapseDimensions`
`protected ParameterSpace<Boolean>`	GlobalPoolingLayerSpace.Builder.`collapseDimensions`
`protected ParameterSpace<Boolean>`	OCNNLayerSpace.`configureR`
`protected ParameterSpace<Boolean>`	OCNNLayerSpace.Builder.`configureR`
`protected ParameterSpace<List<LayerConstraint>>`	FeedForwardLayerSpace.`constrainAll`
`protected ParameterSpace<List<LayerConstraint>>`	FeedForwardLayerSpace.Builder.`constrainAll`
`protected ParameterSpace<List<LayerConstraint>>`	BatchNormalizationSpace.`constrainBeta`
`protected ParameterSpace<List<LayerConstraint>>`	FeedForwardLayerSpace.`constrainBias`
`protected ParameterSpace<List<LayerConstraint>>`	FeedForwardLayerSpace.Builder.`constrainBias`
`protected ParameterSpace<List<LayerConstraint>>`	BatchNormalizationSpace.`constrainGamma`
`protected ParameterSpace<List<LayerConstraint>>`	FeedForwardLayerSpace.`constrainWeights`
`protected ParameterSpace<List<LayerConstraint>>`	FeedForwardLayerSpace.Builder.`constrainWeights`
`protected ParameterSpace<ConvolutionMode>`	SubsamplingLayerSpace.`convolutionMode`
`protected ParameterSpace<ConvolutionMode>`	SubsamplingLayerSpace.Builder.`convolutionMode`
`protected ParameterSpace<ConvolutionMode>`	ConvolutionLayerSpace.`convolutionMode`
`protected ParameterSpace<ConvolutionMode>`	ConvolutionLayerSpace.Builder.`convolutionMode`
`protected ParameterSpace<ConvolutionMode>`	BaseConvolutionLayerSpace.`convolutionMode`
`protected ParameterSpace<ConvolutionMode>`	BaseConvolutionLayerSpace.Builder.`convolutionMode`
`protected ParameterSpace<Double>`	BatchNormalizationSpace.`decay`
`protected ParameterSpace<Double>`	BatchNormalizationSpace.Builder.`decay`
`protected ParameterSpace<int[]>`	SubsamplingLayerSpace.`dilation`
`protected ParameterSpace<int[]>`	SubsamplingLayerSpace.Builder.`dilation`
`protected ParameterSpace<int[]>`	ConvolutionLayerSpace.`dilation`
`protected ParameterSpace<int[]>`	ConvolutionLayerSpace.Builder.`dilation`
`protected ParameterSpace<int[]>`	BaseConvolutionLayerSpace.`dilation`
`protected ParameterSpace<int[]>`	BaseConvolutionLayerSpace.Builder.`dilation`
`protected ParameterSpace<Distribution>`	BaseLayerSpace.`dist`
`protected ParameterSpace<Distribution>`	BaseLayerSpace.Builder.`dist`
`protected ParameterSpace<IDropout>`	LayerSpace.`dropOut`
`protected ParameterSpace<IDropout>`	LayerSpace.Builder.`dropOut`
`protected ParameterSpace<Double>`	SubsamplingLayerSpace.`eps`
`protected ParameterSpace<Double>`	SubsamplingLayerSpace.Builder.`eps`
`protected ParameterSpace<Double>`	BatchNormalizationSpace.`eps`
`protected ParameterSpace<Double>`	BatchNormalizationSpace.Builder.`eps`
`protected ParameterSpace<Double>`	AbstractLSTMLayerSpace.`forgetGateBiasInit`
`protected ParameterSpace<Double>`	BatchNormalizationSpace.`gamma`
`protected ParameterSpace<Double>`	BatchNormalizationSpace.Builder.`gamma`
`protected ParameterSpace<List<LayerConstraint>>`	BatchNormalizationSpace.Builder.`gammaConstraints`
`protected ParameterSpace<IActivation>`	AbstractLSTMLayerSpace.`gateActivationFn`
`protected ParameterSpace<GradientNormalization>`	BaseLayerSpace.`gradientNormalization`
`protected ParameterSpace<GradientNormalization>`	BaseLayerSpace.Builder.`gradientNormalization`
`protected ParameterSpace<Double>`	BaseLayerSpace.`gradientNormalizationThreshold`
`protected ParameterSpace<Double>`	BaseLayerSpace.Builder.`gradientNormalizationThreshold`
`protected ParameterSpace<Boolean>`	EmbeddingLayerSpace.Builder.`hasBias`
`protected ParameterSpace<Boolean>`	DenseLayerSpace.`hasBias`
`protected ParameterSpace<Boolean>`	DenseLayerSpace.Builder.`hasBias`
`protected ParameterSpace<Boolean>`	ConvolutionLayerSpace.`hasBias`
`protected ParameterSpace<Boolean>`	ConvolutionLayerSpace.Builder.`hasBias`
`protected ParameterSpace<Boolean>`	BaseOutputLayerSpace.`hasBias`
`protected ParameterSpace<Boolean>`	BaseOutputLayerSpace.Builder.`hasBias`
`protected ParameterSpace<Boolean>`	BaseConvolutionLayerSpace.`hasBias`
`protected ParameterSpace<Boolean>`	BaseConvolutionLayerSpace.Builder.`hasBias`
`protected ParameterSpace<Integer>`	OCNNLayerSpace.`hiddenLayerSize`
`protected ParameterSpace<Integer>`	OCNNLayerSpace.Builder.`hiddenLayerSize`
`protected ParameterSpace<Double>`	OCNNLayerSpace.`initialRValue`
`protected ParameterSpace<Double>`	OCNNLayerSpace.Builder.`initialRValue`
`protected ParameterSpace<Boolean>`	BatchNormalizationSpace.`isMinibatch`
`protected ParameterSpace<Boolean>`	BatchNormalizationSpace.Builder.`isMinibatch`
`protected ParameterSpace<int[]>`	SubsamplingLayerSpace.`kernelSize`
`protected ParameterSpace<int[]>`	SubsamplingLayerSpace.Builder.`kernelSize`
`protected ParameterSpace<int[]>`	ConvolutionLayerSpace.`kernelSize`
`protected ParameterSpace<int[]>`	ConvolutionLayerSpace.Builder.`kernelSize`
`protected ParameterSpace<int[]>`	BaseConvolutionLayerSpace.`kernelSize`
`protected ParameterSpace<int[]>`	BaseConvolutionLayerSpace.Builder.`kernelSize`
`protected ParameterSpace<Double>`	BaseLayerSpace.`l1`
`protected ParameterSpace<Double>`	BaseLayerSpace.Builder.`l1`
`protected ParameterSpace<Double>`	BaseLayerSpace.`l1Bias`
`protected ParameterSpace<Double>`	BaseLayerSpace.Builder.`l1Bias`
`protected ParameterSpace<Double>`	BaseLayerSpace.`l2`
`protected ParameterSpace<Double>`	BaseLayerSpace.Builder.`l2`
`protected ParameterSpace<Double>`	BaseLayerSpace.`l2Bias`
`protected ParameterSpace<Double>`	BaseLayerSpace.Builder.`l2Bias`
`protected ParameterSpace<Boolean>`	BatchNormalizationSpace.`lockGammaBeta`
`protected ParameterSpace<Boolean>`	BatchNormalizationSpace.Builder.`lockGammaBeta`
`protected ParameterSpace<ILossFunction>`	LossLayerSpace.`lossFunction`
`protected ParameterSpace<ILossFunction>`	LossLayerSpace.Builder.`lossFunction`
`protected ParameterSpace<LossFunctions.LossFunction>`	BasePretrainNetworkLayerSpace.`lossFunction`
`protected ParameterSpace<LossFunctions.LossFunction>`	BasePretrainNetworkLayerSpace.Builder.`lossFunction`
`protected ParameterSpace<ILossFunction>`	BaseOutputLayerSpace.`lossFunction`
`protected ParameterSpace<ILossFunction>`	BaseOutputLayerSpace.Builder.`lossFunction`
`protected ParameterSpace<Integer>`	FeedForwardLayerSpace.`nIn`
`protected ParameterSpace<Integer>`	FeedForwardLayerSpace.Builder.`nIn`
`protected ParameterSpace<Integer>`	FeedForwardLayerSpace.`nOut`
`protected ParameterSpace<Integer>`	FeedForwardLayerSpace.Builder.`nOut`
`protected ParameterSpace<Double>`	OCNNLayerSpace.`nuSpace`
`protected ParameterSpace<Double>`	OCNNLayerSpace.Builder.`nuSpace`
`protected ParameterSpace<int[]>`	SubsamplingLayerSpace.`padding`
`protected ParameterSpace<int[]>`	SubsamplingLayerSpace.Builder.`padding`
`protected ParameterSpace<int[]>`	ConvolutionLayerSpace.`padding`
`protected ParameterSpace<int[]>`	ConvolutionLayerSpace.Builder.`padding`
`protected ParameterSpace<int[]>`	BaseConvolutionLayerSpace.`padding`
`protected ParameterSpace<int[]>`	BaseConvolutionLayerSpace.Builder.`padding`
`protected ParameterSpace<Integer>`	SubsamplingLayerSpace.`pnorm`
`protected ParameterSpace<Integer>`	SubsamplingLayerSpace.Builder.`pnorm`
`protected ParameterSpace<Integer>`	GlobalPoolingLayerSpace.`pNorm`
`protected ParameterSpace<Integer>`	GlobalPoolingLayerSpace.Builder.`pNorm`
`protected ParameterSpace<List<LayerConstraint>>`	SeparableConvolution2DLayerSpace.`pointWiseConstraints`
`protected ParameterSpace<List<LayerConstraint>>`	SeparableConvolution2DLayerSpace.Builder.`pointWiseConstraints`
`protected ParameterSpace<int[]>`	GlobalPoolingLayerSpace.`poolingDimensions`
`protected ParameterSpace<int[]>`	GlobalPoolingLayerSpace.Builder.`poolingDimensions`
`protected ParameterSpace<SubsamplingLayer.PoolingType>`	SubsamplingLayerSpace.`poolingType`
`protected ParameterSpace<SubsamplingLayer.PoolingType>`	SubsamplingLayerSpace.Builder.`poolingType`
`protected ParameterSpace<PoolingType>`	GlobalPoolingLayerSpace.`poolingType`
`protected ParameterSpace<PoolingType>`	GlobalPoolingLayerSpace.Builder.`poolingType`
`protected ParameterSpace<int[]>`	SubsamplingLayerSpace.`stride`
`protected ParameterSpace<int[]>`	SubsamplingLayerSpace.Builder.`stride`
`protected ParameterSpace<int[]>`	ConvolutionLayerSpace.`stride`
`protected ParameterSpace<int[]>`	ConvolutionLayerSpace.Builder.`stride`
`protected ParameterSpace<int[]>`	BaseConvolutionLayerSpace.`stride`
`protected ParameterSpace<int[]>`	BaseConvolutionLayerSpace.Builder.`stride`
`protected ParameterSpace<IUpdater>`	BaseLayerSpace.`updater`
`protected ParameterSpace<IUpdater>`	BaseLayerSpace.Builder.`updater`
`protected ParameterSpace<WeightInit>`	BaseLayerSpace.`weightInit`
`protected ParameterSpace<WeightInit>`	BaseLayerSpace.Builder.`weightInit`
`protected ParameterSpace<IWeightNoise>`	BaseLayerSpace.`weightNoise`
`protected ParameterSpace<IWeightNoise>`	BaseLayerSpace.Builder.`weightNoise`
`protected ParameterSpace<Integer>`	OCNNLayerSpace.`windowSize`
`protected ParameterSpace<Integer>`	OCNNLayerSpace.Builder.`windowSize`

Methods in org.deeplearning4j.arbiter.layers that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	LayerSpace.`collectLeaves()`
`List<ParameterSpace>`	DropoutLayerSpace.`collectLeaves()`
`List<ParameterSpace>`	Bidirectional.`collectLeaves()`

Methods in org.deeplearning4j.arbiter.layers with parameters of type ParameterSpace
Modifier and Type	Method and Description
`LossLayerSpace.Builder`	LossLayerSpace.Builder.`activation(ParameterSpace<Activation> activationFunction)`
`T`	BaseLayerSpace.Builder.`activation(ParameterSpace<Activation> activationFunction)`
`ActivationLayerSpace.Builder`	ActivationLayerSpace.Builder.`activation(ParameterSpace<Activation> activationFunction)`
`LossLayerSpace.Builder`	LossLayerSpace.Builder.`activationFn(ParameterSpace<IActivation> activationFunction)`
`T`	BaseLayerSpace.Builder.`activationFn(ParameterSpace<IActivation> activationFunction)`
`ActivationLayerSpace.Builder`	ActivationLayerSpace.Builder.`activationFn(ParameterSpace<IActivation> activationFunction)`
`LocalResponseNormalizationLayerSpace.Builder`	LocalResponseNormalizationLayerSpace.Builder.`alpha(ParameterSpace<Double> alpha)`
`CenterLossOutputLayerSpace.Builder`	CenterLossOutputLayerSpace.Builder.`alpha(ParameterSpace<Double> alpha)`
`LocalResponseNormalizationLayerSpace.Builder`	LocalResponseNormalizationLayerSpace.Builder.`beta(ParameterSpace<Double> beta)`
`BatchNormalizationSpace.Builder`	BatchNormalizationSpace.Builder.`beta(ParameterSpace<Double> beta)`
`T`	BaseLayerSpace.Builder.`biasInit(ParameterSpace<Double> biasInit)`
`T`	BaseLayerSpace.Builder.`biasUpdater(ParameterSpace<IUpdater> biasUpdater)`
`GlobalPoolingLayerSpace.Builder`	GlobalPoolingLayerSpace.Builder.`collapseDimensions(ParameterSpace<Boolean> collapseDimensions)`
`OCNNLayerSpace.Builder`	OCNNLayerSpace.Builder.`configureR(ParameterSpace<Boolean> configureR)`
`T`	FeedForwardLayerSpace.Builder.`constrainAllParams(ParameterSpace<List<LayerConstraint>> constraints)`
`BatchNormalizationSpace.Builder`	BatchNormalizationSpace.Builder.`constrainBeta(ParameterSpace<List<LayerConstraint>> constraints)`
`T`	FeedForwardLayerSpace.Builder.`constrainBias(ParameterSpace<List<LayerConstraint>> constraints)`
`BatchNormalizationSpace.Builder`	BatchNormalizationSpace.Builder.`constrainGamma(ParameterSpace<List<LayerConstraint>> constraints)`
`SeparableConvolution2DLayerSpace.Builder`	SeparableConvolution2DLayerSpace.Builder.`constrainPointWise(ParameterSpace<List<LayerConstraint>> constraints)`
`T`	FeedForwardLayerSpace.Builder.`constrainWeights(ParameterSpace<List<LayerConstraint>> constraints)`
`SubsamplingLayerSpace.Builder`	SubsamplingLayerSpace.Builder.`convolutionMode(ParameterSpace<ConvolutionMode> convolutionMode)`
`ConvolutionLayerSpace.Builder`	ConvolutionLayerSpace.Builder.`convolutionMode(ParameterSpace<ConvolutionMode> convolutionMode)`
`T`	BaseConvolutionLayerSpace.Builder.`convolutionMode(ParameterSpace<ConvolutionMode> convolutionMode)`
`AutoEncoderLayerSpace.Builder`	AutoEncoderLayerSpace.Builder.`corruptionLevel(ParameterSpace<Double> corruptionLevel)`
`BatchNormalizationSpace.Builder`	BatchNormalizationSpace.Builder.`decay(ParameterSpace<Double> decay)`
`VariationalAutoencoderLayerSpace.Builder`	VariationalAutoencoderLayerSpace.Builder.`decoderLayerSizes(ParameterSpace<int[]> decoderLayerSizes)`
`SeparableConvolution2DLayerSpace.Builder`	SeparableConvolution2DLayerSpace.Builder.`depthMultiplier(ParameterSpace<Integer> depthMultiplier)`
`SubsamplingLayerSpace.Builder`	SubsamplingLayerSpace.Builder.`dilation(ParameterSpace<int[]> dilation)`
`ConvolutionLayerSpace.Builder`	ConvolutionLayerSpace.Builder.`dilation(ParameterSpace<int[]> dilation)`
`T`	BaseConvolutionLayerSpace.Builder.`dilation(ParameterSpace<int[]> dilation)`
`T`	BaseLayerSpace.Builder.`dist(ParameterSpace<Distribution> dist)`
`T`	LayerSpace.Builder.`dropOut(ParameterSpace<Double> dropOut)`
`DropoutLayerSpace.Builder`	DropoutLayerSpace.Builder.`dropOut(ParameterSpace<Double> dropOut)`
`VariationalAutoencoderLayerSpace.Builder`	VariationalAutoencoderLayerSpace.Builder.`encoderLayerSizes(ParameterSpace<int[]> encoderLayerSizes)`
`SubsamplingLayerSpace.Builder`	SubsamplingLayerSpace.Builder.`eps(ParameterSpace<Double> eps)`
`BatchNormalizationSpace.Builder`	BatchNormalizationSpace.Builder.`eps(ParameterSpace<Double> eps)`
`GravesBidirectionalLSTMLayerSpace.Builder`	GravesBidirectionalLSTMLayerSpace.Builder.`forgetGateBiasInit(ParameterSpace<Double> forgetGateBiasInit)`
`T`	AbstractLSTMLayerSpace.Builder.`forgetGateBiasInit(ParameterSpace<Double> forgetGateBiasInit)`
`BatchNormalizationSpace.Builder`	BatchNormalizationSpace.Builder.`gamma(ParameterSpace<Double> gamma)`
`T`	AbstractLSTMLayerSpace.Builder.`gateActivation(ParameterSpace<Activation> gateActivationFn)`
`T`	AbstractLSTMLayerSpace.Builder.`gateActivationFn(ParameterSpace<IActivation> gateActivationFn)`
`T`	BaseLayerSpace.Builder.`gradientNormalization(ParameterSpace<GradientNormalization> gradientNormalization)`
`T`	BaseLayerSpace.Builder.`gradientNormalizationThreshold(ParameterSpace<Double> gradientNormalizationThreshold)`
`EmbeddingLayerSpace.Builder`	EmbeddingLayerSpace.Builder.`hasBias(ParameterSpace<Boolean> hasBias)`
`DenseLayerSpace.Builder`	DenseLayerSpace.Builder.`hasBias(ParameterSpace<Boolean> hasBias)`
`ConvolutionLayerSpace.Builder`	ConvolutionLayerSpace.Builder.`hasBias(ParameterSpace<Boolean> hasBias)`
`T`	BaseOutputLayerSpace.Builder.`hasBias(ParameterSpace<Boolean> hasBias)`
`T`	BaseConvolutionLayerSpace.Builder.`hasBias(ParameterSpace<Boolean> hasBias)`
`OCNNLayerSpace.Builder`	OCNNLayerSpace.Builder.`hiddenLayerSize(ParameterSpace<Integer> hiddenLayerSize)`
`T`	LayerSpace.Builder.`iDropOut(ParameterSpace<IDropout> dropOut)`
`DropoutLayerSpace.Builder`	DropoutLayerSpace.Builder.`iDropOut(ParameterSpace<IDropout> dropout)`
`LossLayerSpace.Builder`	LossLayerSpace.Builder.`iLossFunction(ParameterSpace<ILossFunction> lossFunction)`
`T`	BaseOutputLayerSpace.Builder.`iLossFunction(ParameterSpace<ILossFunction> lossFunction)`
`OCNNLayerSpace.Builder`	OCNNLayerSpace.Builder.`initialRValue(ParameterSpace<Double> initialRValue)`
`LocalResponseNormalizationLayerSpace.Builder`	LocalResponseNormalizationLayerSpace.Builder.`k(ParameterSpace<Double> k)`
`SubsamplingLayerSpace.Builder`	SubsamplingLayerSpace.Builder.`kernelSize(ParameterSpace<int[]> kernelSize)`
`ConvolutionLayerSpace.Builder`	ConvolutionLayerSpace.Builder.`kernelSize(ParameterSpace<int[]> kernelSize)`
`T`	BaseConvolutionLayerSpace.Builder.`kernelSize(ParameterSpace<int[]> kernelSize)`
`T`	BaseLayerSpace.Builder.`l1(ParameterSpace<Double> l1)`
`T`	BaseLayerSpace.Builder.`l1Bias(ParameterSpace<Double> l1Bias)`
`T`	BaseLayerSpace.Builder.`l2(ParameterSpace<Double> l2)`
`T`	BaseLayerSpace.Builder.`l2Bias(ParameterSpace<Double> l2Bias)`
`CenterLossOutputLayerSpace.Builder`	CenterLossOutputLayerSpace.Builder.`lambda(ParameterSpace<Double> lambda)`
`BatchNormalizationSpace.Builder`	BatchNormalizationSpace.Builder.`lockGammaBeta(ParameterSpace<Boolean> lockGammaBeta)`
`LossLayerSpace.Builder`	LossLayerSpace.Builder.`lossFunction(ParameterSpace<LossFunctions.LossFunction> lossFunction)`
`T`	BasePretrainNetworkLayerSpace.Builder.`lossFunction(ParameterSpace<LossFunctions.LossFunction> lossFunction)`
`T`	BaseOutputLayerSpace.Builder.`lossFunction(ParameterSpace<LossFunctions.LossFunction> lossFunction)`
`BatchNormalizationSpace.Builder`	BatchNormalizationSpace.Builder.`minibatch(ParameterSpace<Boolean> minibatch)`
`LocalResponseNormalizationLayerSpace.Builder`	LocalResponseNormalizationLayerSpace.Builder.`n(ParameterSpace<Double> n)`
`T`	FeedForwardLayerSpace.Builder.`nIn(ParameterSpace<Integer> nIn)`
`T`	FeedForwardLayerSpace.Builder.`nOut(ParameterSpace<Integer> nOut)`
`OCNNLayerSpace.Builder`	OCNNLayerSpace.Builder.`nu(ParameterSpace<Double> nuSpace)`
`OCNNLayerSpace.Builder`	OCNNLayerSpace.Builder.`numHidden(ParameterSpace<Integer> numHiddenSpace)` Deprecated.
`VariationalAutoencoderLayerSpace.Builder`	VariationalAutoencoderLayerSpace.Builder.`numSamples(ParameterSpace<Integer> numSamples)`
`SubsamplingLayerSpace.Builder`	SubsamplingLayerSpace.Builder.`padding(ParameterSpace<int[]> padding)`
`ConvolutionLayerSpace.Builder`	ConvolutionLayerSpace.Builder.`padding(ParameterSpace<int[]> padding)`
`T`	BaseConvolutionLayerSpace.Builder.`padding(ParameterSpace<int[]> padding)`
`SubsamplingLayerSpace.Builder`	SubsamplingLayerSpace.Builder.`pnorm(ParameterSpace<Integer> pnorm)`
`GlobalPoolingLayerSpace.Builder`	GlobalPoolingLayerSpace.Builder.`pNorm(ParameterSpace<Integer> pNorm)`
`GlobalPoolingLayerSpace.Builder`	GlobalPoolingLayerSpace.Builder.`poolingDimensions(ParameterSpace<int[]> poolingDimensions)`
`GlobalPoolingLayerSpace.Builder`	GlobalPoolingLayerSpace.Builder.`poolingType(ParameterSpace<PoolingType> poolingType)`
`SubsamplingLayerSpace.Builder`	SubsamplingLayerSpace.Builder.`poolingType(ParameterSpace<SubsamplingLayer.PoolingType> poolingType)`
`VariationalAutoencoderLayerSpace.Builder`	VariationalAutoencoderLayerSpace.Builder.`pzxActivationFn(ParameterSpace<IActivation> activationFunction)`
`VariationalAutoencoderLayerSpace.Builder`	VariationalAutoencoderLayerSpace.Builder.`reconstructionDistribution(ParameterSpace<ReconstructionDistribution> distribution)`
`AutoEncoderLayerSpace.Builder`	AutoEncoderLayerSpace.Builder.`sparsity(ParameterSpace<Double> sparsity)`
`SubsamplingLayerSpace.Builder`	SubsamplingLayerSpace.Builder.`stride(ParameterSpace<int[]> stride)`
`ConvolutionLayerSpace.Builder`	ConvolutionLayerSpace.Builder.`stride(ParameterSpace<int[]> stride)`
`T`	BaseConvolutionLayerSpace.Builder.`stride(ParameterSpace<int[]> stride)`
`T`	BaseLayerSpace.Builder.`updater(ParameterSpace<IUpdater> updater)`
`T`	BaseLayerSpace.Builder.`weightInit(ParameterSpace<WeightInit> weightInit)`
`OCNNLayerSpace.Builder`	OCNNLayerSpace.Builder.`windowSize(ParameterSpace<Integer> windowSize)`

Constructors in org.deeplearning4j.arbiter.layers with parameters of type ParameterSpace
Constructor and Description
`DropoutLayerSpace(ParameterSpace<IDropout> dropout)`

Uses of ParameterSpace in org.deeplearning4j.arbiter.layers.fixed

Classes in org.deeplearning4j.arbiter.layers.fixed that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`FixedLayerSpace<T extends Layer>` A layer space that wraps a DL4J layer, without any optimizable hyperparameters

Methods in org.deeplearning4j.arbiter.layers.fixed that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	FixedLayerSpace.`collectLeaves()`

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.api

Classes in org.deeplearning4j.arbiter.optimize.api that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`AbstractParameterSpace<T>` Created by Alex on 23/07/2017.

Methods in org.deeplearning4j.arbiter.optimize.api that return ParameterSpace
Modifier and Type	Method and Description
`ParameterSpace<?>`	CandidateGenerator.`getParameterSpace()`

Methods in org.deeplearning4j.arbiter.optimize.api that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	ParameterSpace.`collectLeaves()` Collect a list of parameters, recursively.
`Map<String,ParameterSpace>`	ParameterSpace.`getNestedSpaces()` Get a list of nested parameter spaces by name.
`Map<String,ParameterSpace>`	AbstractParameterSpace.`getNestedSpaces()`

Method parameters in org.deeplearning4j.arbiter.optimize.api with type arguments of type ParameterSpace
Modifier and Type	Method and Description
`static TaskCreator`	TaskCreatorProvider.`defaultTaskCreatorFor(Class<? extends ParameterSpace> paramSpaceClass)`
`static void`	TaskCreatorProvider.`registerDefaultTaskCreatorClass(Class<? extends ParameterSpace> spaceClass, Class<? extends TaskCreator> creatorClass)`

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.api.adapter

Classes in org.deeplearning4j.arbiter.optimize.api.adapter that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`ParameterSpaceAdapter<F,T>` An abstract class used for adapting one type into another.

Methods in org.deeplearning4j.arbiter.optimize.api.adapter that return ParameterSpace
Modifier and Type	Method and Description
`protected abstract ParameterSpace<F>`	ParameterSpaceAdapter.`underlying()`

Methods in org.deeplearning4j.arbiter.optimize.api.adapter that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	ParameterSpaceAdapter.`collectLeaves()`
`Map<String,ParameterSpace>`	ParameterSpaceAdapter.`getNestedSpaces()`

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.generator

Fields in org.deeplearning4j.arbiter.optimize.generator declared as ParameterSpace
Modifier and Type	Field and Description
`protected ParameterSpace<?>`	GeneticSearchCandidateGenerator.Builder.`parameterSpace`
`protected ParameterSpace<T>`	BaseCandidateGenerator.`parameterSpace`

Methods in org.deeplearning4j.arbiter.optimize.generator that return ParameterSpace
Modifier and Type	Method and Description
`ParameterSpace<T>`	BaseCandidateGenerator.`getParameterSpace()`

Constructors in org.deeplearning4j.arbiter.optimize.generator with parameters of type ParameterSpace
Constructor and Description
`BaseCandidateGenerator(ParameterSpace<T> parameterSpace, Map<String,Object> dataParameters, boolean initDone)`
`Builder(ParameterSpace<?> parameterSpace, ScoreFunction scoreFunction)`
`GridSearchCandidateGenerator(ParameterSpace<?> parameterSpace, int discretizationCount, GridSearchCandidateGenerator.Mode mode, Map<String,Object> dataParameters)`
`GridSearchCandidateGenerator(ParameterSpace<?> parameterSpace, int discretizationCount, GridSearchCandidateGenerator.Mode mode, Map<String,Object> dataParameters, boolean initDone)`
`RandomSearchGenerator(ParameterSpace<?> parameterSpace)`
`RandomSearchGenerator(ParameterSpace<?> parameterSpace, Map<String,Object> dataParameters)`
`RandomSearchGenerator(ParameterSpace<?> parameterSpace, Map<String,Object> dataParameters, boolean initDone)`

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter

Classes in org.deeplearning4j.arbiter.optimize.parameter that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`BooleanSpace` BooleanParameterSpace is a `ParameterSpace<Boolean>`; Defines {True, False} as a parameter space If argument to setValue is less than or equal to 0.5 it will return True else False
`class`	`FixedValue<T>` FixedValue is a ParameterSpace that defines only a single fixed value

Methods in org.deeplearning4j.arbiter.optimize.parameter that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	FixedValue.`collectLeaves()`
`List<ParameterSpace>`	BooleanSpace.`collectLeaves()`
`Map<String,ParameterSpace>`	FixedValue.`getNestedSpaces()`
`Map<String,ParameterSpace>`	BooleanSpace.`getNestedSpaces()`

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter.continuous

Classes in org.deeplearning4j.arbiter.optimize.parameter.continuous that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`ContinuousParameterSpace` ContinuousParametSpace is a `ParameterSpace<Double>` that (optionally) takes an Apache Commons `RealDistribution` when used for random sampling (such as in a RandomSearchCandidateGenerator)

Methods in org.deeplearning4j.arbiter.optimize.parameter.continuous that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	ContinuousParameterSpace.`collectLeaves()`
`Map<String,ParameterSpace>`	ContinuousParameterSpace.`getNestedSpaces()`

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter.discrete

Classes in org.deeplearning4j.arbiter.optimize.parameter.discrete that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`DiscreteParameterSpace<P>` A DiscreteParameterSpace is used for a set of un-ordered values

Methods in org.deeplearning4j.arbiter.optimize.parameter.discrete that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	DiscreteParameterSpace.`collectLeaves()`
`Map<String,ParameterSpace>`	DiscreteParameterSpace.`getNestedSpaces()`

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter.integer

Classes in org.deeplearning4j.arbiter.optimize.parameter.integer that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`IntegerParameterSpace` IntegerParameterSpace is a `ParameterSpace<Integer>`; i.e., defines an ordered space of integers between some minimum and maximum value

Methods in org.deeplearning4j.arbiter.optimize.parameter.integer that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	IntegerParameterSpace.`collectLeaves()`
`Map<String,ParameterSpace>`	IntegerParameterSpace.`getNestedSpaces()`

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter.math

Classes in org.deeplearning4j.arbiter.optimize.parameter.math that implement ParameterSpace
Modifier and Type	Class and Description
`class`	`MathOp<T extends Number>` A simple parameter space that implements scalar mathematical operations on another parameter space.
`class`	`PairMathOp<T extends Number>` A simple parameter space that implements pairwise mathematical operations on another parameter space.

Methods in org.deeplearning4j.arbiter.optimize.parameter.math that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`List<ParameterSpace>`	PairMathOp.`collectLeaves()`
`List<ParameterSpace>`	MathOp.`collectLeaves()`

Constructors in org.deeplearning4j.arbiter.optimize.parameter.math with parameters of type ParameterSpace
Constructor and Description
`MathOp(ParameterSpace<T> parameterSpace, Op op, T scalar)`
`PairMathOp(ParameterSpace<T> first, ParameterSpace<T> second, Op op)`
`PairMathOp(ParameterSpace<T> first, ParameterSpace<T> second, Op op)`

Uses of ParameterSpace in org.deeplearning4j.arbiter.util

Methods in org.deeplearning4j.arbiter.util that return types with arguments of type ParameterSpace
Modifier and Type	Method and Description
`static List<ParameterSpace>`	LeafUtils.`getUniqueObjects(List<ParameterSpace> allLeaves)` Returns a list of unique objects, not using the .equals() method, but rather using ==

Method parameters in org.deeplearning4j.arbiter.util with type arguments of type ParameterSpace
Modifier and Type	Method and Description
`static int`	LeafUtils.`countUniqueParameters(List<ParameterSpace> allLeaves)` Count the number of unique parameters in the specified leaf nodes
`static List<ParameterSpace>`	LeafUtils.`getUniqueObjects(List<ParameterSpace> allLeaves)` Returns a list of unique objects, not using the .equals() method, but rather using ==

Uses of Interfaceorg.deeplearning4j.arbiter.optimize.api.ParameterSpace

Uses of ParameterSpace in org.deeplearning4j.arbiter

Uses of ParameterSpace in org.deeplearning4j.arbiter.adapter

Uses of ParameterSpace in org.deeplearning4j.arbiter.conf.dropout

Uses of ParameterSpace in org.deeplearning4j.arbiter.conf.updater

Uses of ParameterSpace in org.deeplearning4j.arbiter.conf.updater.schedule

Uses of ParameterSpace in org.deeplearning4j.arbiter.dropout

Uses of ParameterSpace in org.deeplearning4j.arbiter.layers

Uses of ParameterSpace in org.deeplearning4j.arbiter.layers.fixed

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.api

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.api.adapter

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.generator

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter.continuous

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter.discrete

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter.integer

Uses of ParameterSpace in org.deeplearning4j.arbiter.optimize.parameter.math

Uses of ParameterSpace in org.deeplearning4j.arbiter.util

Uses of Interface
org.deeplearning4j.arbiter.optimize.api.ParameterSpace