Uses of Class
org.deeplearning4j.berkeley.Pair

Packages that use Pair

Package	Description
org.deeplearning4j.berkeley
org.deeplearning4j.datasets.iterator
org.deeplearning4j.eval
org.deeplearning4j.nn.api
org.deeplearning4j.nn.api.layers
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.feedforward.autoencoder
org.deeplearning4j.nn.layers.feedforward.embedding
org.deeplearning4j.nn.layers.feedforward.rbm
org.deeplearning4j.nn.layers.normalization
org.deeplearning4j.nn.layers.recurrent
org.deeplearning4j.nn.multilayer
org.deeplearning4j.optimize.api
org.deeplearning4j.optimize.listeners
org.deeplearning4j.optimize.solvers
org.deeplearning4j.util

Uses of Pair in org.deeplearning4j.berkeley

Methods in org.deeplearning4j.berkeley that return Pair

Modifier and Type	Method and Description
Pair<K,V>	CounterMap.argMax() Finds the key with maximum count.
static <S,T> Pair<S,T>	Pair.makePair(S first, T second)
static <S,T> Pair<S,T>	Pair.newPair(S first, T second)
Pair<S,F>	Pair.reverse()

Methods in org.deeplearning4j.berkeley that return types with arguments of type Pair

Modifier and Type	Method and Description
Iterator<Pair<K,V>>	CounterMap.getPairIterator()
static <S,T> Iterator<Pair<S,T>>	Iterators.zip(Iterator<S> s, Iterator<T> t)

Methods in org.deeplearning4j.berkeley with parameters of type Pair

Modifier and Type	Method and Description
int	Pair.LexicographicPairComparator.compare(Pair<F,S> pair1, Pair<F,S> pair2)
int	Pair.LexicographicPairComparator.compare(Pair<F,S> pair1, Pair<F,S> pair2)
int	Pair.DefaultLexicographicPairComparator.compare(Pair<F,S> o1, Pair<F,S> o2)
int	Pair.DefaultLexicographicPairComparator.compare(Pair<F,S> o1, Pair<F,S> o2)
int	Pair.FirstComparator.compare(Pair<S,T> p1, Pair<S,T> p2)
int	Pair.FirstComparator.compare(Pair<S,T> p1, Pair<S,T> p2)
int	Pair.ReverseFirstComparator.compare(Pair<S,T> p1, Pair<S,T> p2)
int	Pair.ReverseFirstComparator.compare(Pair<S,T> p1, Pair<S,T> p2)
int	Pair.SecondComparator.compare(Pair<S,T> p1, Pair<S,T> p2)
int	Pair.SecondComparator.compare(Pair<S,T> p1, Pair<S,T> p2)
int	Pair.ReverseSecondComparator.compare(Pair<S,T> p1, Pair<S,T> p2)
int	Pair.ReverseSecondComparator.compare(Pair<S,T> p1, Pair<S,T> p2)
int	Pair.compareTo(Pair<F,S> o) Compares this object with the specified object for order.

Uses of Pair in org.deeplearning4j.datasets.iterator

Constructor parameters in org.deeplearning4j.datasets.iterator with type arguments of type Pair

Constructor and Description
AbstractDataSetIterator(Iterable<Pair<T,T>> iterable, int batchSize)
DoublesDataSetIterator(Iterable<Pair<double[],double[]>> iterable, int batchSize)
FloatsDataSetIterator(Iterable<Pair<float[],float[]>> iterable, int batchSize)
INDArrayDataSetIterator(Iterable<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> iterable, int batchSize)

Uses of Pair in org.deeplearning4j.eval

Fields in org.deeplearning4j.eval with type parameters of type Pair

Modifier and Type	Field and Description
protected Map<Pair<Integer,Integer>,List<Object>>	Evaluation.confusionMatrixMetaData

Uses of Pair in org.deeplearning4j.nn.api

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	Layer.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon) Calculate the gradient relative to the error in the next layer
Pair<Gradient,Double>	Model.gradientAndScore() Get the gradient and score

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

Methods in org.deeplearning4j.nn.api.layers that return Pair

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	RecurrentLayer.tbpttBackpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon, int tbpttBackLength) Truncated BPTT equivalent of Layer.backpropGradient().

Uses of Pair in org.deeplearning4j.nn.graph

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

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

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

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	GraphVertex.doBackward(boolean tbptt) Do backward pass

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

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	StackVertex.doBackward(boolean tbptt)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	LayerVertex.doBackward(boolean tbptt)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	SubsetVertex.doBackward(boolean tbptt)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	PreprocessorVertex.doBackward(boolean tbptt)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	UnstackVertex.doBackward(boolean tbptt)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	MergeVertex.doBackward(boolean tbptt)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	ElementWiseVertex.doBackward(boolean tbptt)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	InputVertex.doBackward(boolean tbptt)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	L2Vertex.doBackward(boolean tbptt)

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

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	LastTimeStepVertex.doBackward(boolean tbptt)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray[]>	DuplicateToTimeSeriesVertex.doBackward(boolean tbptt)

Uses of Pair in org.deeplearning4j.nn.layers

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	BasePretrainNetwork.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	LossLayer.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	BaseLayer.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	BaseOutputLayer.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	ActivationLayer.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,Double>	LossLayer.gradientAndScore()
Pair<Gradient,Double>	BaseLayer.gradientAndScore()
Pair<Gradient,Double>	BaseOutputLayer.gradientAndScore()
abstract Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>	BasePretrainNetwork.sampleHiddenGivenVisible(org.nd4j.linalg.api.ndarray.INDArray v) Sample the hidden distribution given the visible
abstract Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>	BasePretrainNetwork.sampleVisibleGivenHidden(org.nd4j.linalg.api.ndarray.INDArray h) Sample the visible distribution given the hidden

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

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	ConvolutionLayer.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	ConvolutionHelper.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray input, org.nd4j.linalg.api.ndarray.INDArray weights, org.nd4j.linalg.api.ndarray.INDArray delta, int[] kernel, int[] strides, int[] pad, org.nd4j.linalg.api.ndarray.INDArray biasGradView, org.nd4j.linalg.api.ndarray.INDArray weightGradView, String afn, ConvolutionLayer.AlgoMode mode, ConvolutionMode convolutionMode)

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

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	SubsamplingLayer.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	SubsamplingHelper.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray input, org.nd4j.linalg.api.ndarray.INDArray epsilon, int[] kernel, int[] strides, int[] pad, SubsamplingLayer.PoolingType poolingType, ConvolutionMode convolutionMode)

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

Methods in org.deeplearning4j.nn.layers.feedforward.autoencoder that return Pair

Modifier and Type	Method and Description
Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>	AutoEncoder.sampleHiddenGivenVisible(org.nd4j.linalg.api.ndarray.INDArray v)
Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>	AutoEncoder.sampleVisibleGivenHidden(org.nd4j.linalg.api.ndarray.INDArray h)

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

Methods in org.deeplearning4j.nn.layers.feedforward.embedding that return Pair

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	EmbeddingLayer.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)

Uses of Pair in org.deeplearning4j.nn.layers.feedforward.rbm

Methods in org.deeplearning4j.nn.layers.feedforward.rbm that return Pair

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	RBM.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>,Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>>	RBM.gibbhVh(org.nd4j.linalg.api.ndarray.INDArray h) Gibbs sampling step: hidden ---> visible ---> hidden
Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>	RBM.sampleHiddenGivenVisible(org.nd4j.linalg.api.ndarray.INDArray v) Binomial sampling of the hidden values given visible
Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>	RBM.sampleVisibleGivenHidden(org.nd4j.linalg.api.ndarray.INDArray h) Guess the visible values given the hidden

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

Modifier and Type	Method and Description
Pair<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>,Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>>	RBM.gibbhVh(org.nd4j.linalg.api.ndarray.INDArray h) Gibbs sampling step: hidden ---> visible ---> hidden
Pair<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>,Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>>	RBM.gibbhVh(org.nd4j.linalg.api.ndarray.INDArray h) Gibbs sampling step: hidden ---> visible ---> hidden

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

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	BatchNormalization.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	LocalResponseNormalization.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	LocalResponseNormalizationHelper.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray input, org.nd4j.linalg.api.ndarray.INDArray epsilon, double k, double n, double alpha, double beta)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	BatchNormalizationHelper.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray input, org.nd4j.linalg.api.ndarray.INDArray epsilon, int[] shape, org.nd4j.linalg.api.ndarray.INDArray gamma, org.nd4j.linalg.api.ndarray.INDArray dGammaView, org.nd4j.linalg.api.ndarray.INDArray dBetaView, double eps)

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

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	GravesLSTM.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	GravesBidirectionalLSTM.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	RnnOutputLayer.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
static Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	LSTMHelpers.backpropGradientHelper(NeuralNetConfiguration conf, org.nd4j.linalg.api.ndarray.INDArray input, org.nd4j.linalg.api.ndarray.INDArray recurrentWeights, org.nd4j.linalg.api.ndarray.INDArray inputWeights, org.nd4j.linalg.api.ndarray.INDArray epsilon, boolean truncatedBPTT, int tbpttBackwardLength, FwdPassReturn fwdPass, boolean forwards, String inputWeightKey, String recurrentWeightKey, String biasWeightKey, Map<String,org.nd4j.linalg.api.ndarray.INDArray> gradientViews)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	GravesLSTM.tbpttBackpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon, int tbpttBackwardLength)
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	GravesBidirectionalLSTM.tbpttBackpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon, int tbpttBackwardLength)

Uses of Pair in org.deeplearning4j.nn.multilayer

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

Modifier and Type	Method and Description
Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	MultiLayerNetwork.backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)
protected Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	MultiLayerNetwork.calcBackpropGradients(org.nd4j.linalg.api.ndarray.INDArray epsilon, boolean withOutputLayer) Calculate gradients and errors.
Pair<Gradient,Double>	MultiLayerNetwork.gradientAndScore()

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

Modifier and Type	Method and Description
protected List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>>	MultiLayerNetwork.computeDeltas2()
List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>>	MultiLayerNetwork.unPack(org.nd4j.linalg.api.ndarray.INDArray param) Deprecated. use MultiLayerNetwork.setParameters(INDArray)

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

Modifier and Type	Method and Description
org.nd4j.linalg.api.ndarray.INDArray	MultiLayerNetwork.pack(List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> layers) Deprecated. use MultiLayerNetwork.params()

Uses of Pair in org.deeplearning4j.optimize.api

Methods in org.deeplearning4j.optimize.api that return Pair

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

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

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

Uses of Pair in org.deeplearning4j.optimize.listeners

Methods in org.deeplearning4j.optimize.listeners that return types with arguments of type Pair

Modifier and Type	Method and Description
List<Pair<Integer,Double>>	CollectScoresIterationListener.getScoreVsIter()

Uses of Pair in org.deeplearning4j.optimize.solvers

Methods in org.deeplearning4j.optimize.solvers that return Pair

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

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

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

Uses of Pair in org.deeplearning4j.util

Methods in org.deeplearning4j.util that return Pair

Modifier and Type	Method and Description
Pair<Double,org.nd4j.linalg.api.ndarray.INDArray>	Viterbi.decode(org.nd4j.linalg.api.ndarray.INDArray labels) Decodes the given labels, assuming its a binary label matrix
Pair<Double,org.nd4j.linalg.api.ndarray.INDArray>	Viterbi.decode(org.nd4j.linalg.api.ndarray.INDArray labels, boolean binaryLabelMatrix) Decodes a series of labels
Pair<K,T>	MultiDimensionalMap.Entry.getKey() Returns the key corresponding to this entry.

Methods in org.deeplearning4j.util that return types with arguments of type Pair

Modifier and Type	Method and Description
Iterator<Pair<K,V>>	MultiDimensionalSet.iterator() Returns an iterator over the elements in this applyTransformToDestination.
Set<Pair<K,T>>	MultiDimensionalMap.keySet() Returns a Set view of the keys contained in this map.

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

Modifier and Type	Method and Description
boolean	MultiDimensionalSet.add(Pair<K,V> kvPair) Adds the specified element to this applyTransformToDestination if it is not already present (optional operation).
V	MultiDimensionalMap.put(Pair<K,T> key, V value) Associates the specified value with the specified key in this map (optional operation).

Method parameters in org.deeplearning4j.util with type arguments of type Pair

Modifier and Type	Method and Description
boolean	MultiDimensionalSet.addAll(Collection<? extends Pair<K,V>> c) Adds all of the elements in the specified collection to this applyTransformToDestination if they're not already present (optional operation).
void	MultiDimensionalMap.putAll(Map<? extends Pair<K,T>,? extends V> m) Copies all of the mappings from the specified map to this map (optional operation).
static void	InputSplit.splitInputs(org.nd4j.linalg.api.ndarray.INDArray inputs, org.nd4j.linalg.api.ndarray.INDArray outcomes, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> train, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> test, double split)
static void	InputSplit.splitInputs(org.nd4j.linalg.api.ndarray.INDArray inputs, org.nd4j.linalg.api.ndarray.INDArray outcomes, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> train, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> test, double split)
static void	InputSplit.splitInputs(List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> pairs, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> train, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> test, double split)
static void	InputSplit.splitInputs(List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> pairs, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> train, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> test, double split)
static void	InputSplit.splitInputs(List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> pairs, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> train, List<Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>> test, double split)

Constructor parameters in org.deeplearning4j.util with type arguments of type Pair

Constructor and Description
MultiDimensionalMap(Map<Pair<K,T>,V> backedMap)
MultiDimensionalSet(Set<Pair<K,V>> backedSet)