Uses of Class
org.nd4j.common.primitives.Pair

Packages that use Pair

Package	Description
org.datavec.api.timeseries.util
org.datavec.arrow
org.datavec.hadoop.records.reader.mapfile
org.datavec.hadoop.records.reader.mapfile.index
org.datavec.image.loader
org.datavec.image.transform
org.datavec.local.transforms.functions
org.datavec.local.transforms.functions.data
org.datavec.local.transforms.join
org.datavec.local.transforms.misc
org.datavec.local.transforms.misc.comparator
org.datavec.local.transforms.rank
org.datavec.local.transforms.reduce
org.datavec.local.transforms.sequence
org.datavec.nlp.movingwindow
org.datavec.spark.transform
org.deeplearning4j.clustering.cluster
org.deeplearning4j.clustering.kdtree
org.deeplearning4j.clustering.randomprojection
org.deeplearning4j.iterator
org.deeplearning4j.iterator.bert
org.deeplearning4j.iterator.provider
org.deeplearning4j.models.embeddings.loader
org.deeplearning4j.models.fasttext
org.deeplearning4j.models.paragraphvectors
org.deeplearning4j.nlp.uima.corpora.treeparser
org.deeplearning4j.nn.api
org.deeplearning4j.nn.api.layers
org.deeplearning4j.nn.conf
org.deeplearning4j.nn.conf.graph
org.deeplearning4j.nn.conf.layers
org.deeplearning4j.nn.conf.layers.samediff
org.deeplearning4j.nn.conf.preprocessor
org.deeplearning4j.nn.graph
org.deeplearning4j.nn.graph.vertex
org.deeplearning4j.nn.graph.vertex.impl
org.deeplearning4j.nn.graph.vertex.impl.rnn
org.deeplearning4j.nn.layers
org.deeplearning4j.nn.layers.convolution
org.deeplearning4j.nn.layers.convolution.subsampling
org.deeplearning4j.nn.layers.convolution.upsampling
org.deeplearning4j.nn.layers.feedforward
org.deeplearning4j.nn.layers.feedforward.autoencoder
org.deeplearning4j.nn.layers.feedforward.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.modelimport.keras.layers
org.deeplearning4j.nn.modelimport.keras.preprocessing.sequence
org.deeplearning4j.nn.modelimport.keras.utils
org.deeplearning4j.nn.multilayer
org.deeplearning4j.optimize.api
org.deeplearning4j.optimize.solvers
org.deeplearning4j.parallelism.inference
org.deeplearning4j.parallelism.inference.observers
org.deeplearning4j.plot
org.deeplearning4j.rl4j.network.ac
org.deeplearning4j.rl4j.util
org.deeplearning4j.spark.api
org.deeplearning4j.spark.impl.paramavg
org.deeplearning4j.spark.models.embeddings.word2vec
org.deeplearning4j.spark.models.sequencevectors.functions
org.deeplearning4j.spark.parameterserver.training
org.deeplearning4j.spark.text.functions
org.deeplearning4j.text.invertedindex
org.deeplearning4j.text.movingwindow
org.deeplearning4j.ui.model.stats.api
org.deeplearning4j.ui.model.stats.impl
org.deeplearning4j.ui.model.stats.impl.java
org.deeplearning4j.util
org.deeplearning4j.zoo.model.helper
org.nd4j.aeron.ipc
org.nd4j.autodiff.execution.input
org.nd4j.autodiff.samediff
org.nd4j.autodiff.samediff.internal
org.nd4j.common.collection
org.nd4j.common.function
org.nd4j.common.primitives
org.nd4j.evaluation
org.nd4j.evaluation.classification
org.nd4j.graph.ui
org.nd4j.linalg.activations
org.nd4j.linalg.activations.impl
org.nd4j.linalg.api.ndarray
org.nd4j.linalg.api.ops
org.nd4j.linalg.cache
org.nd4j.linalg.checkutil
org.nd4j.linalg.cpu.nativecpu
org.nd4j.linalg.cpu.nativecpu.ops
org.nd4j.linalg.dataset.api
org.nd4j.linalg.factory
org.nd4j.linalg.lossfunctions
org.nd4j.linalg.lossfunctions.impl
org.nd4j.parameterserver.distributed
org.nd4j.parameterserver.distributed.v2
org.nd4j.remote.grpc
org.nd4j.serde.binary
org.nd4j.systeminfo

Uses of Pair in org.datavec.api.timeseries.util

Methods in org.datavec.api.timeseries.util that return Pair

Modifier and Type	Method and Description
static Pair<INDArray,INDArray>	TimeSeriesWritableUtils.convertWritablesSequence(List<List<List<Writable>>> timeSeriesRecord) Convert the writables to a sequence (3d) data set, and also return the mask array (if necessary)
static Pair<INDArray,INDArray>	TimeSeriesWritableUtils.convertWritablesSequence(List<List<List<Writable>>> list, TimeSeriesWritableUtils.RecordDetails details) Convert the writables to a sequence (3d) data set, and also return the mask array (if necessary)

Uses of Pair in org.datavec.arrow

Methods in org.datavec.arrow that return Pair

Modifier and Type	Method and Description
static Pair<Schema,ArrowWritableRecordBatch>	ArrowConverter.readFromBytes(byte[] input) Read a datavec schema and record set from the given bytes (usually expected to be an arrow format file)
static Pair<Schema,ArrowWritableRecordBatch>	ArrowConverter.readFromFile(File input) Read a datavec schema and record set from the given arrow file.
static Pair<Schema,ArrowWritableRecordBatch>	ArrowConverter.readFromFile(FileInputStream input) Read a datavec schema and record set from the given arrow file.

Uses of Pair in org.datavec.hadoop.records.reader.mapfile

Methods in org.datavec.hadoop.records.reader.mapfile that return types with arguments of type Pair

Modifier and Type	Method and Description
List<Pair<Long,Long>>	IndexToKey.initialize(org.apache.hadoop.io.MapFile.Reader[] readers, Class<? extends org.apache.hadoop.io.Writable> valueClass) Initialise the instance, and return the first and last record indexes (inclusive) for each reader

Uses of Pair in org.datavec.hadoop.records.reader.mapfile.index

Methods in org.datavec.hadoop.records.reader.mapfile.index that return types with arguments of type Pair

Modifier and Type	Method and Description
List<Pair<Long,Long>>	LongIndexToKey.initialize(org.apache.hadoop.io.MapFile.Reader[] readers, Class<? extends org.apache.hadoop.io.Writable> valueClass)

Uses of Pair in org.datavec.image.loader

Methods in org.datavec.image.loader that return Pair

Modifier and Type	Method and Description
Pair<INDArray,org.bytedeco.opencv.opencv_core.Mat>	CifarLoader.convertMat(byte[] byteFeature)

Uses of Pair in org.datavec.image.transform

Fields in org.datavec.image.transform with type parameters of type Pair

Modifier and Type	Field and Description
protected List<Pair<ImageTransform,Double>>	PipelineImageTransform.imageTransforms
protected List<Pair<ImageTransform,Double>>	PipelineImageTransform.Builder.imageTransforms

Constructor parameters in org.datavec.image.transform with type arguments of type Pair

Constructor and Description
PipelineImageTransform(List<Pair<ImageTransform,Double>> transforms)
PipelineImageTransform(List<Pair<ImageTransform,Double>> transforms, boolean shuffle)
PipelineImageTransform(long seed, List<Pair<ImageTransform,Double>> transforms)
PipelineImageTransform(long seed, List<Pair<ImageTransform,Double>> transforms, boolean shuffle)
PipelineImageTransform(Random random, long seed, List<Pair<ImageTransform,Double>> transforms, boolean shuffle)

Uses of Pair in org.datavec.local.transforms.functions

Methods in org.datavec.local.transforms.functions with parameters of type Pair

Modifier and Type	Method and Description
List<Writable>	RecordReaderFunction.apply(Pair<String,InputStream> value)
List<List<Writable>>	SequenceRecordReaderFunction.apply(Pair<String,InputStream> value)

Uses of Pair in org.datavec.local.transforms.functions.data

Methods in org.datavec.local.transforms.functions.data that return Pair

Modifier and Type	Method and Description
Pair<Text,BytesWritable>	FilesAsBytesFunction.apply(Pair<String,InputStream> in)

Methods in org.datavec.local.transforms.functions.data with parameters of type Pair

Modifier and Type	Method and Description
Pair<Text,BytesWritable>	FilesAsBytesFunction.apply(Pair<String,InputStream> in)
List<Writable>	RecordReaderBytesFunction.apply(Pair<Text,BytesWritable> v1)
List<List<Writable>>	SequenceRecordReaderBytesFunction.apply(Pair<Text,BytesWritable> v1)

Uses of Pair in org.datavec.local.transforms.join

Methods in org.datavec.local.transforms.join that return Pair

Modifier and Type	Method and Description
Pair<List<Writable>,List<Writable>>	ExtractKeysFunction.apply(List<Writable> writables)

Methods in org.datavec.local.transforms.join with parameters of type Pair

Modifier and Type	Method and Description
List<List<Writable>>	ExecuteJoinFromCoGroupFlatMapFunctionAdapter.call(Pair<List<Writable>,Pair<List<List<Writable>>,List<List<Writable>>>> t2)

Method parameters in org.datavec.local.transforms.join with type arguments of type Pair

Modifier and Type	Method and Description
List<List<Writable>>	ExecuteJoinFromCoGroupFlatMapFunctionAdapter.call(Pair<List<Writable>,Pair<List<List<Writable>>,List<List<Writable>>>> t2)

Uses of Pair in org.datavec.local.transforms.misc

Methods in org.datavec.local.transforms.misc that return Pair

Modifier and Type	Method and Description
Pair<Writable,List<Writable>>	ColumnAsKeyPairFunction.apply(List<Writable> writables)
Pair<Writable,Long>	ColumnToKeyPairTransform.apply(List<Writable> list)

Methods in org.datavec.local.transforms.misc with parameters of type Pair

Modifier and Type	Method and Description
Long	SumLongsFunction2.apply(Pair<Long,Long> input)
List<List<Writable>>	SequenceMergeFunction.apply(Pair<T,Iterable<List<List<Writable>>>> t2)

Uses of Pair in org.datavec.local.transforms.misc.comparator

Methods in org.datavec.local.transforms.misc.comparator with parameters of type Pair

Modifier and Type	Method and Description
int	Tuple2Comparator.compare(Pair<T,Long> o1, Pair<T,Long> o2)
int	Tuple2Comparator.compare(Pair<T,Long> o1, Pair<T,Long> o2)

Uses of Pair in org.datavec.local.transforms.rank

Methods in org.datavec.local.transforms.rank with parameters of type Pair

Modifier and Type	Method and Description
List<Writable>	UnzipForCalculateSortedRankFunction.apply(Pair<Pair<Writable,List<Writable>>,Long> v1)

Method parameters in org.datavec.local.transforms.rank with type arguments of type Pair

Modifier and Type	Method and Description
List<Writable>	UnzipForCalculateSortedRankFunction.apply(Pair<Pair<Writable,List<Writable>>,Long> v1)

Uses of Pair in org.datavec.local.transforms.reduce

Methods in org.datavec.local.transforms.reduce that return Pair

Modifier and Type	Method and Description
Pair<String,List<Writable>>	MapToPairForReducerFunction.apply(List<Writable> writables)

Uses of Pair in org.datavec.local.transforms.sequence

Methods in org.datavec.local.transforms.sequence that return Pair

Modifier and Type	Method and Description
Pair<Writable,List<Writable>>	LocalMapToPairByColumnFunction.apply(List<Writable> writables)
Pair<List<Writable>,List<Writable>>	LocalMapToPairByMultipleColumnsFunction.apply(List<Writable> writables)

Uses of Pair in org.datavec.nlp.movingwindow

Methods in org.datavec.nlp.movingwindow that return Pair

Modifier and Type	Method and Description
static Pair<String,MultiDimensionalMap<Integer,Integer,String>>	ContextLabelRetriever.stringWithLabels(String sentence, TokenizerFactory tokenizerFactory) Returns a stripped sentence with the indices of words with certain kinds of labels.

Uses of Pair in org.datavec.spark.transform

Methods in org.datavec.spark.transform that return Pair

Modifier and Type	Method and Description
static Pair<Schema,org.apache.spark.api.java.JavaRDD<List<Writable>>>	DataFrames.toRecords(org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> dataFrame) Create a compatible schema and rdd for datavec
static Pair<Schema,org.apache.spark.api.java.JavaRDD<List<List<Writable>>>>	DataFrames.toRecordsSequence(org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> dataFrame) Convert the given DataFrame to a sequence Note: It is assumed here that the DataFrame has been created by DataFrames.toDataFrameSequence(Schema, JavaRDD).

Uses of Pair in org.deeplearning4j.clustering.cluster

Methods in org.deeplearning4j.clustering.cluster that return Pair

Modifier and Type	Method and Description
Pair<Double,Long>	CentersHolder.getCenterByMinDistance(Point point, Distance distanceFunction)
Pair<Cluster,Double>	ClusterSet.nearestCluster(Point point)

Uses of Pair in org.deeplearning4j.clustering.kdtree

Methods in org.deeplearning4j.clustering.kdtree that return Pair

Modifier and Type	Method and Description
Pair<Double,INDArray>	KDTree.nn(INDArray point) Query for nearest neighbor.
static Pair<float[],float[]>	HyperRect.point(INDArray vector)

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

Modifier and Type	Method and Description
List<Pair<Float,INDArray>>	KDTree.knn(INDArray point, float distance)

Constructors in org.deeplearning4j.clustering.kdtree with parameters of type Pair

Constructor and Description
HyperRect(Pair<float[],float[]> ends)

Uses of Pair in org.deeplearning4j.clustering.randomprojection

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

Modifier and Type	Method and Description
static List<Pair<Double,Integer>>	RPUtils.queryAllWithDistances(INDArray toQuery, INDArray X, List<RPTree> trees, int n, String similarityFunction) Query all trees using the given input and data
List<Pair<Double,Integer>>	RPForest.queryWithDistances(INDArray query, int numResults) Query all with the distances sorted by index
List<Pair<Double,Integer>>	RPTree.queryWithDistances(INDArray query, int numResults) Query all with the distances sorted by index
static List<Pair<Double,Integer>>	RPUtils.sortCandidates(INDArray x, INDArray X, List<Integer> candidates, String similarityFunction) Get the sorted distances given the query vector, input data, given the list of possible search candidates

Uses of Pair in org.deeplearning4j.iterator

Methods in org.deeplearning4j.iterator that return Pair

Modifier and Type	Method and Description
Pair<INDArray[],INDArray[]>	BertIterator.featurizeSentencePairs(List<Pair<String,String>> listOnlySentencePairs) For use during inference.
Pair<INDArray[],INDArray[]>	BertIterator.featurizeSentences(List<String> listOnlySentences) For use during inference.
Pair<String,String>	LabeledSentenceProvider.nextSentence()

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

Modifier and Type	Method and Description
Pair<INDArray[],INDArray[]>	BertIterator.featurizeSentencePairs(List<Pair<String,String>> listOnlySentencePairs) For use during inference.

Uses of Pair in org.deeplearning4j.iterator.bert

Methods in org.deeplearning4j.iterator.bert that return Pair

Modifier and Type	Method and Description
Pair<List<String>,boolean[]>	BertMaskedLMMasker.maskSequence(List<String> input, String maskToken, List<String> vocabWords)
Pair<List<String>,boolean[]>	BertSequenceMasker.maskSequence(List<String> input, String maskToken, List<String> vocabWords)

Uses of Pair in org.deeplearning4j.iterator.provider

Methods in org.deeplearning4j.iterator.provider that return Pair

Modifier and Type	Method and Description
Pair<String,String>	CollectionLabeledSentenceProvider.nextSentence()
Pair<String,String>	FileLabeledSentenceProvider.nextSentence()
Pair<String,String>	LabelAwareConverter.nextSentence()

Uses of Pair in org.deeplearning4j.models.embeddings.loader

Methods in org.deeplearning4j.models.embeddings.loader that return Pair

Modifier and Type	Method and Description
static Pair<InMemoryLookupTable,VocabCache>	WordVectorSerializer.loadTxt(@NonNull File file)
static Pair<InMemoryLookupTable,VocabCache>	WordVectorSerializer.loadTxt(@NonNull InputStream inputStream) Loads an in memory cache from the given input stream (sets syn0 and the vocab).
Pair<VocabWord,float[]>	WordVectorSerializer.Reader.next()
Pair<VocabWord,float[]>	WordVectorSerializer.BinaryReader.next()
Pair<VocabWord,float[]>	WordVectorSerializer.CSVReader.next()

Methods in org.deeplearning4j.models.embeddings.loader with parameters of type Pair

Modifier and Type	Method and Description
static Word2Vec	WordVectorSerializer.fromPair(Pair<InMemoryLookupTable,VocabCache> pair) Load word vectors from the given pair

Uses of Pair in org.deeplearning4j.models.fasttext

Methods in org.deeplearning4j.models.fasttext that return Pair

Modifier and Type	Method and Description
Pair<String,Float>	FastText.predictProbability(String text)

Uses of Pair in org.deeplearning4j.models.paragraphvectors

Methods in org.deeplearning4j.models.paragraphvectors that return Pair

Modifier and Type	Method and Description
Pair<String,INDArray>	ParagraphVectors.InferenceCallable.call()

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

Modifier and Type	Method and Description
Future<Pair<String,INDArray>>	ParagraphVectors.inferVectorBatched(@NonNull LabelledDocument document) This method implements batched inference, based on Java Future parallelism model.

Uses of Pair in org.deeplearning4j.nlp.uima.corpora.treeparser

Methods in org.deeplearning4j.nlp.uima.corpora.treeparser with parameters of type Pair

Modifier and Type	Method and Description
static Tree	TreeFactory.buildTree(org.cleartk.syntax.constituent.type.TreebankNode node, Pair<String,MultiDimensionalMap<Integer,Integer,String>> labels, List<String> possibleLabels) Builds a tree recursively adding the children as necessary
static Tree	TreeFactory.toTree(org.cleartk.syntax.constituent.type.TreebankNode node, Pair<String,MultiDimensionalMap<Integer,Integer,String>> labels) Converts a treebank node to a tree

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,INDArray>	Layer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr) Calculate the gradient relative to the error in the next layer
Pair<INDArray,MaskState>	Layer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize) Feed forward the input mask array, setting in the layer as appropriate.
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,INDArray>	RecurrentLayer.tbpttBackpropGradient(INDArray epsilon, int tbpttBackLength, LayerWorkspaceMgr workspaceMgr) Truncated BPTT equivalent of Layer.backpropGradient().

Uses of Pair in org.deeplearning4j.nn.conf

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

Modifier and Type	Method and Description
Pair<INDArray,MaskState>	InputPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)

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

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

Modifier and Type	Method and Description
Pair<INDArray,MaskState>	AttentionVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)

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

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

Modifier and Type	Method and Description
Pair<INDArray,MaskState>	LearnedSelfAttentionLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)

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

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

Modifier and Type	Method and Description
Pair<INDArray,MaskState>	SameDiffLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	SameDiffVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)

Uses of Pair in org.deeplearning4j.nn.conf.preprocessor

Methods in org.deeplearning4j.nn.conf.preprocessor that return Pair

Modifier and Type	Method and Description
Pair<INDArray,MaskState>	BaseInputPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	Cnn3DToFeedForwardPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	CnnToFeedForwardPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	CnnToRnnPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	ComposableInputPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	FeedForwardToCnn3DPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	FeedForwardToCnnPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	FeedForwardToRnnPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	RnnToCnnPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	RnnToFeedForwardPreProcessor.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)

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,INDArray[]>	BaseWrapperVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray[]>	GraphVertex.doBackward(boolean tbptt, LayerWorkspaceMgr workspaceMgr) Do backward pass
Pair<INDArray,MaskState>	BaseWrapperVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	GraphVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)

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,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)
Pair<INDArray,MaskState>	ElementWiseVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	InputVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	L2NormalizeVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	L2Vertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	LayerVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	MergeVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	PoolHelperVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	PreprocessorVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	ReshapeVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	ScaleVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	ShiftVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	StackVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	SubsetVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	UnstackVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)

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,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)
Pair<INDArray,MaskState>	DuplicateToTimeSeriesVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	LastTimeStepVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	ReverseTimeSeriesVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)

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,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<INDArray,MaskState>	AbstractLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<Gradient,Double>	AbstractLayer.gradientAndScore()
Pair<Gradient,Double>	BaseOutputLayer.gradientAndScore()
Pair<Gradient,Double>	FrozenLayer.gradientAndScore()
Pair<Gradient,Double>	LossLayer.gradientAndScore()
protected Pair<INDArray,INDArray>	BaseLayer.preOutputWithPreNorm(boolean training, boolean forBackprop, LayerWorkspaceMgr workspaceMgr)
abstract Pair<INDArray,INDArray>	BasePretrainNetwork.sampleHiddenGivenVisible(INDArray v) Sample the hidden distribution given the visible
abstract Pair<INDArray,INDArray>	BasePretrainNetwork.sampleVisibleGivenHidden(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,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>	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>	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)
protected Pair<INDArray,INDArray>	Convolution1DLayer.causalConv1dForward()
Pair<INDArray,MaskState>	Cnn3DLossLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	CnnLossLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	Convolution1DLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	ConvolutionLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
protected Pair<INDArray,INDArray>	Convolution1DLayer.preOutput(boolean training, boolean forBackprop, LayerWorkspaceMgr workspaceMgr)
protected Pair<INDArray,INDArray>	Convolution3DLayer.preOutput(boolean training, boolean forBackprop, LayerWorkspaceMgr workspaceMgr)
protected Pair<INDArray,INDArray>	ConvolutionLayer.preOutput(boolean training, boolean forBackprop, LayerWorkspaceMgr workspaceMgr) PreOutput method that also returns the im2col2d array (if being called for backprop), as this can be re-used instead of being calculated again.
protected Pair<INDArray,INDArray>	Deconvolution2DLayer.preOutput(boolean training, boolean forBackprop, LayerWorkspaceMgr workspaceMgr)
protected Pair<INDArray,INDArray>	DepthwiseConvolution2DLayer.preOutput(boolean training, boolean forBackprop, LayerWorkspaceMgr workspaceMgr)
protected Pair<INDArray,INDArray>	SeparableConvolution2DLayer.preOutput(boolean training, boolean forBackprop, LayerWorkspaceMgr workspaceMgr)
protected Pair<INDArray,INDArray>	Convolution1DLayer.preOutput4d(boolean training, boolean forBackprop, LayerWorkspaceMgr workspaceMgr)
protected Pair<INDArray,INDArray>	ConvolutionLayer.preOutput4d(boolean training, boolean forBackprop, LayerWorkspaceMgr workspaceMgr) preOutput4d: Used so that ConvolutionLayer subclasses (such as Convolution1DLayer) can maintain their standard non-4d preOutput method, while overriding this to return 4d activations (for use in backprop) without modifying the public API

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,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>	Subsampling1DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	Subsampling3DLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	SubsamplingLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<INDArray,MaskState>	Subsampling1DLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	SubsamplingLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)

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

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

Modifier and Type	Method and 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 Pair in org.deeplearning4j.nn.layers.feedforward

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

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

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<INDArray,INDArray>	AutoEncoder.sampleHiddenGivenVisible(INDArray v)
Pair<INDArray,INDArray>	AutoEncoder.sampleVisibleGivenHidden(INDArray h)

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

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

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

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,INDArray>	EmbeddingLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	EmbeddingSequenceLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

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

Modifier and Type	Method and Description
Pair<Gradient,INDArray>	MKLDNNLocalResponseNormalizationHelper.backpropGradient(INDArray input, INDArray epsilon, double k, double n, double alpha, double beta, 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>	MKLDNNSubsamplingHelper.backpropGradient(INDArray input, INDArray epsilon, int[] kernel, int[] strides, int[] pad, PoolingType poolingType, ConvolutionMode convolutionMode, int[] dilation, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr)
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>	MKLDNNLSTMHelper.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)

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,INDArray>	LocalResponseNormalizationHelper.backpropGradient(INDArray input, INDArray epsilon, double k, double n, double alpha, double beta, 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>	BatchNormalization.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Gradient,INDArray>	LocalResponseNormalization.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)

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

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

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

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

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

Modifier and Type	Method and Description
Pair<Gradient,INDArray>	OCNNOutputLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<Double,INDArray>	OCNNOutputLayer.OCNNLossFunction.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)

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

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

Modifier and Type	Method and Description
Pair<Gradient,INDArray>	GlobalPoolingLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<INDArray,MaskState>	GlobalPoolingLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)

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,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>	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)
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)
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<INDArray,MaskState>	BidirectionalLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	GravesBidirectionalLSTM.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	GravesLSTM.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize) Deprecated.
Pair<INDArray,MaskState>	LastTimeStepLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	LSTM.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	MaskZeroLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	RnnLossLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	RnnOutputLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	TimeDistributedLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
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)

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

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

Modifier and Type	Method and 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)
Pair<INDArray,MaskState>	SameDiffLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<INDArray,MaskState>	SameDiffGraphVertex.feedForwardMaskArrays(INDArray[] maskArrays, MaskState currentMaskState, int minibatchSize)

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

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

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

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

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

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

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

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

Modifier and Type	Method and Description
Pair<Gradient,INDArray>	VariationalAutoencoder.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<INDArray,MaskState>	VariationalAutoencoder.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<Gradient,Double>	VariationalAutoencoder.gradientAndScore()

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

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

Modifier and Type	Method and Description
Pair<Gradient,INDArray>	BaseWrapperLayer.backpropGradient(INDArray epsilon, LayerWorkspaceMgr workspaceMgr)
Pair<INDArray,MaskState>	BaseWrapperLayer.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<Gradient,Double>	BaseWrapperLayer.gradientAndScore()

Uses of Pair in org.deeplearning4j.nn.modelimport.keras.layers

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

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

Uses of Pair in org.deeplearning4j.nn.modelimport.keras.preprocessing.sequence

Methods in org.deeplearning4j.nn.modelimport.keras.preprocessing.sequence that return Pair

Modifier and Type	Method and Description
Pair<INDArray,INDArray>	TimeSeriesGenerator.next(int index)

Uses of Pair in org.deeplearning4j.nn.modelimport.keras.utils

Methods in org.deeplearning4j.nn.modelimport.keras.utils that return Pair

Modifier and Type	Method and Description
static Pair<Boolean,Double>	KerasLayerUtils.getMaskingConfiguration(List<String> inboundLayerNames, Map<String,? extends KerasLayer> previousLayers)

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,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<INDArray,MaskState>	MultiLayerNetwork.feedForwardMaskArray(INDArray maskArray, MaskState currentMaskState, int minibatchSize)
Pair<Gradient,Double>	MultiLayerNetwork.gradientAndScore()

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(LayerWorkspaceMgr workspaceMgr) 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.solvers

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

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

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.parallelism.inference

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

Modifier and Type	Method and Description
List<Pair<INDArray[],INDArray[]>>	InferenceObservable.getInputBatches() Get input batches - and their associated input mask arrays, if any Note that usually the returned list will be of size 1 - however, in the batched case, not all inputs can actually be batched (variable size inputs to fully convolutional net, for example).

Uses of Pair in org.deeplearning4j.parallelism.inference.observers

Methods in org.deeplearning4j.parallelism.inference.observers that return types with arguments of type Pair

Modifier and Type	Method and Description
List<Pair<INDArray[],INDArray[]>>	BasicInferenceObservable.getInputBatches()
List<Pair<INDArray[],INDArray[]>>	BatchedInferenceObservable.getInputBatches()

Uses of Pair in org.deeplearning4j.plot

Methods in org.deeplearning4j.plot that return Pair

Modifier and Type	Method and Description
Pair<INDArray,Double>	BarnesHutTsne.computeGaussianKernel(INDArray distances, double beta, int k) Computes a gaussian kernel given a vector of squared distance distances
protected Pair<Double,INDArray>	BarnesHutTsne.gradient(INDArray p)
Pair<Gradient,Double>	BarnesHutTsne.gradientAndScore()
Pair<Double,INDArray>	Tsne.hBeta(INDArray d, double beta) Computes a gaussian kernel given a vector of squared distance distances

Uses of Pair in org.deeplearning4j.rl4j.network.ac

Methods in org.deeplearning4j.rl4j.network.ac that return Pair

Modifier and Type	Method and Description
Pair<Double,INDArray>	ActorCriticLoss.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)

Uses of Pair in org.deeplearning4j.rl4j.util

Methods in org.deeplearning4j.rl4j.util that return Pair

Modifier and Type	Method and Description
static <C> Pair<IDQN,C>	DataManager.load(File file, Class<C> cClass)
static <C> Pair<IDQN,C>	DataManager.load(InputStream is, Class<C> cClass)
static <C> Pair<IDQN,C>	DataManager.load(String path, Class<C> cClass)

Uses of Pair in org.deeplearning4j.spark.api

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

Modifier and Type	Method and Description
Pair<R,SparkTrainingStats>	TrainingWorker.getFinalResultNoDataWithStats() As per TrainingWorker.getFinalResultNoData() but used when SparkTrainingStats are being collected
Pair<R,SparkTrainingStats>	TrainingWorker.getFinalResultWithStats(ComputationGraph graph) As per TrainingWorker.getFinalResult(ComputationGraph) but used when SparkTrainingStats are being collected
Pair<R,SparkTrainingStats>	TrainingWorker.getFinalResultWithStats(MultiLayerNetwork network) As per TrainingWorker.getFinalResult(MultiLayerNetwork) but used when SparkTrainingStats are being collected
Pair<R,SparkTrainingStats>	TrainingWorker.processMinibatchWithStats(DataSet dataSet, ComputationGraph graph, boolean isLast) As per TrainingWorker.processMinibatch(DataSet, ComputationGraph, boolean) but used when SparkTrainingStats are being collected
Pair<R,SparkTrainingStats>	TrainingWorker.processMinibatchWithStats(DataSet dataSet, MultiLayerNetwork network, boolean isLast) As per TrainingWorker.processMinibatch(DataSet, MultiLayerNetwork, boolean) but used when SparkTrainingStats are being collecte
Pair<R,SparkTrainingStats>	TrainingWorker.processMinibatchWithStats(MultiDataSet dataSet, ComputationGraph graph, boolean isLast) As per TrainingWorker.processMinibatch(MultiDataSet, ComputationGraph, boolean) but used when SparkTrainingStats are being collected

Uses of Pair in org.deeplearning4j.spark.impl.paramavg

Methods in org.deeplearning4j.spark.impl.paramavg that return Pair

Modifier and Type	Method and Description
Pair<ParameterAveragingTrainingResult,SparkTrainingStats>	ParameterAveragingTrainingWorker.getFinalResultNoDataWithStats()
Pair<ParameterAveragingTrainingResult,SparkTrainingStats>	ParameterAveragingTrainingWorker.getFinalResultWithStats(ComputationGraph graph)
Pair<ParameterAveragingTrainingResult,SparkTrainingStats>	ParameterAveragingTrainingWorker.getFinalResultWithStats(MultiLayerNetwork network)
Pair<ParameterAveragingTrainingResult,SparkTrainingStats>	ParameterAveragingTrainingWorker.processMinibatchWithStats(DataSet dataSet, ComputationGraph graph, boolean isLast)
Pair<ParameterAveragingTrainingResult,SparkTrainingStats>	ParameterAveragingTrainingWorker.processMinibatchWithStats(DataSet dataSet, MultiLayerNetwork network, boolean isLast)
Pair<ParameterAveragingTrainingResult,SparkTrainingStats>	ParameterAveragingTrainingWorker.processMinibatchWithStats(MultiDataSet dataSet, ComputationGraph graph, boolean isLast)

Uses of Pair in org.deeplearning4j.spark.models.embeddings.word2vec

Methods in org.deeplearning4j.spark.models.embeddings.word2vec that return Pair

Modifier and Type	Method and Description
Pair<VocabWord,INDArray>	MapToPairFunction.call(Map.Entry<VocabWord,INDArray> pair)

Methods in org.deeplearning4j.spark.models.embeddings.word2vec with parameters of type Pair

Modifier and Type	Method and Description
void	Word2VecPerformer.call(Pair<List<VocabWord>,AtomicLong> pair) Deprecated.
void	Word2VecPerformerVoid.call(Pair<List<VocabWord>,AtomicLong> pair) Deprecated.

Uses of Pair in org.deeplearning4j.spark.models.sequencevectors.functions

Methods in org.deeplearning4j.spark.models.sequencevectors.functions that return Pair

Modifier and Type	Method and Description
Pair<Sequence<T>,Long>	CountFunction.call(Sequence<T> sequence)
Pair<Sequence<T>,Long>	ExtraCountFunction.call(Sequence<T> sequence)

Uses of Pair in org.deeplearning4j.spark.parameterserver.training

Methods in org.deeplearning4j.spark.parameterserver.training that return Pair

Modifier and Type	Method and Description
Pair<SharedTrainingResult,SparkTrainingStats>	SharedTrainingWorker.getFinalResultNoDataWithStats()
Pair<SharedTrainingResult,SparkTrainingStats>	SharedTrainingWorker.getFinalResultWithStats(ComputationGraph graph)
Pair<SharedTrainingResult,SparkTrainingStats>	SharedTrainingWorker.getFinalResultWithStats(MultiLayerNetwork network)
Pair<SharedTrainingResult,SparkTrainingStats>	SharedTrainingWorker.processMinibatchWithStats(DataSet dataSet, ComputationGraph graph, boolean isLast)
Pair<SharedTrainingResult,SparkTrainingStats>	SharedTrainingWorker.processMinibatchWithStats(DataSet dataSet, MultiLayerNetwork network, boolean isLast)
Pair<SharedTrainingResult,SparkTrainingStats>	SharedTrainingWorker.processMinibatchWithStats(MultiDataSet dataSet, ComputationGraph graph, boolean isLast)

Uses of Pair in org.deeplearning4j.spark.text.functions

Methods in org.deeplearning4j.spark.text.functions that return Pair

Modifier and Type	Method and Description
Pair<List<String>,AtomicLong>	UpdateWordFreqAccumulatorFunction.call(List<String> lstOfWords)

Methods in org.deeplearning4j.spark.text.functions that return types with arguments of type Pair

Modifier and Type	Method and Description
org.apache.spark.api.java.JavaRDD<Pair<List<String>,AtomicLong>>	TextPipeline.getSentenceWordsCountRDD()
org.apache.spark.api.java.JavaRDD<Pair<List<String>,AtomicLong>>	TextPipeline.updateAndReturnAccumulatorVal(org.apache.spark.api.java.JavaRDD<List<String>> tokenizedRDD)

Methods in org.deeplearning4j.spark.text.functions with parameters of type Pair

Modifier and Type	Method and Description
AtomicLong	GetSentenceCountFunction.call(Pair<List<String>,AtomicLong> pair)
List<VocabWord>	WordsListToVocabWordsFunction.call(Pair<List<String>,AtomicLong> pair)

Uses of Pair in org.deeplearning4j.text.invertedindex

Methods in org.deeplearning4j.text.invertedindex that return Pair

Modifier and Type	Method and Description
Pair<List<T>,String>	InvertedIndex.documentWithLabel(int index) Returns a list of words for a document and the associated label
Pair<List<T>,Collection<String>>	InvertedIndex.documentWithLabels(int index) Returns a list of words associated with the document and the associated labels

Method parameters in org.deeplearning4j.text.invertedindex with type arguments of type Pair

Modifier and Type	Method and Description
void	InvertedIndex.eachDocWithLabel(org.nd4j.shade.guava.base.Function<Pair<List<T>,String>,Void> func, Executor exec) Iterate over each document with a label
void	InvertedIndex.eachDocWithLabels(org.nd4j.shade.guava.base.Function<Pair<List<T>,Collection<String>>,Void> func, Executor exec) Iterate over each document with a label

Uses of Pair in org.deeplearning4j.text.movingwindow

Methods in org.deeplearning4j.text.movingwindow that return Pair

Modifier and Type	Method and Description
static Pair<String,MultiDimensionalMap<Integer,Integer,String>>	ContextLabelRetriever.stringWithLabels(String sentence, TokenizerFactory tokenizerFactory) Returns a stripped sentence with the indices of words with certain kinds of labels.

Uses of Pair in org.deeplearning4j.ui.model.stats.api

Methods in org.deeplearning4j.ui.model.stats.api that return types with arguments of type Pair

Modifier and Type	Method and Description
List<Pair<String,int[]>>	StatsReport.getGarbageCollectionStats() Get the garbage collection stats: Pair contains GC name and the delta count/time values

Uses of Pair in org.deeplearning4j.ui.model.stats.impl

Methods in org.deeplearning4j.ui.model.stats.impl that return types with arguments of type Pair

Modifier and Type	Method and Description
List<Pair<String,int[]>>	SbeStatsReport.getGarbageCollectionStats()

Uses of Pair in org.deeplearning4j.ui.model.stats.impl.java

Methods in org.deeplearning4j.ui.model.stats.impl.java that return types with arguments of type Pair

Modifier and Type	Method and Description
List<Pair<String,int[]>>	JavaStatsReport.getGarbageCollectionStats()

Uses of Pair in org.deeplearning4j.util

Methods in org.deeplearning4j.util that return Pair

Modifier and Type	Method and Description
static Pair<INDArray,int[]>	TimeSeriesUtils.pullLastTimeSteps(INDArray pullFrom, INDArray mask) Extract out the last time steps (2d array from 3d array input) accounting for the mask layer, if present.
static Pair<INDArray,int[]>	TimeSeriesUtils.pullLastTimeSteps(INDArray pullFrom, INDArray mask, LayerWorkspaceMgr workspaceMgr, ArrayType arrayType) Extract out the last time steps (2d array from 3d array input) accounting for the mask layer, if present.
static Pair<ComputationGraph,Normalizer>	ModelSerializer.restoreComputationGraphAndNormalizer(@NonNull File file, boolean loadUpdater) Restore a ComputationGraph and Normalizer (if present - null if not) from a File
static Pair<ComputationGraph,Normalizer>	ModelSerializer.restoreComputationGraphAndNormalizer(@NonNull InputStream is, boolean loadUpdater) Restore a ComputationGraph and Normalizer (if present - null if not) from the InputStream.
static Pair<MultiLayerNetwork,Normalizer>	ModelSerializer.restoreMultiLayerNetworkAndNormalizer(@NonNull File file, boolean loadUpdater) Restore a MultiLayerNetwork and Normalizer (if present - null if not) from a File
static Pair<MultiLayerNetwork,Normalizer>	ModelSerializer.restoreMultiLayerNetworkAndNormalizer(@NonNull InputStream is, boolean loadUpdater) Restore a MultiLayerNetwork and Normalizer (if present - null if not) from the InputStream.

Uses of Pair in org.deeplearning4j.zoo.model.helper

Methods in org.deeplearning4j.zoo.model.helper that return Pair

Modifier and Type	Method and Description
static Pair<String,String>	NASNetHelper.normalA(ComputationGraphConfiguration.GraphBuilder graphBuilder, int filters, String blockId, String inputX, String inputP)
static Pair<String,String>	NASNetHelper.reductionA(ComputationGraphConfiguration.GraphBuilder graphBuilder, int filters, String blockId, String inputX, String inputP)

Uses of Pair in org.nd4j.aeron.ipc

Methods in org.nd4j.aeron.ipc that return Pair

Modifier and Type	Method and Description
static Pair<INDArray,ByteBuffer>	AeronNDArraySerde.toArrayAndByteBuffer(org.agrona.DirectBuffer buffer, int offset) Create an ndarray from the unsafe buffer.

Uses of Pair in org.nd4j.autodiff.execution.input

Methods in org.nd4j.autodiff.execution.input that return types with arguments of type Pair

Modifier and Type	Method and Description
Collection<Pair<Operands.NodeDescriptor,INDArray>>	Operands.asCollection() This method returns contents of this entity as collection of key->value pairs

Uses of Pair in org.nd4j.autodiff.samediff

Methods in org.nd4j.autodiff.samediff that return Pair

Modifier and Type	Method and Description
static Pair<String,Integer>	SameDiff.parseVariable(@NonNull String varName) Note: INTENDED FOR DEVELOPER USE This method extract base variable name and output index (if exists) from raw variable name.

Uses of Pair in org.nd4j.autodiff.samediff.internal

Methods in org.nd4j.autodiff.samediff.internal that return Pair

Modifier and Type	Method and Description
Pair<SameDiffOp,OpContext>	InferenceSession.getAndParameterizeOp(String opName, FrameIter frameIter, Set<AbstractSession.VarId> opInputs, Set<AbstractSession.VarId> allIterInputs, Set<String> constAndPhInputs, Map<String,INDArray> placeholderValues, Set<String> allReqVariables)

Methods in org.nd4j.autodiff.samediff.internal with parameters of type Pair

Modifier and Type	Method and Description
INDArray[]	InferenceSession.getOutputs(Pair<SameDiffOp,OpContext> opPair, FrameIter outputFrameIter, Set<AbstractSession.VarId> opInputs, Set<AbstractSession.VarId> allIterInputs, Set<String> constAndPhInputs, List<Listener> listeners, At at, MultiDataSet batch, Set<String> allReqVariables)
INDArray[]	TrainingSession.getOutputs(Pair<SameDiffOp,OpContext> opPair, FrameIter outputFrameIter, Set<AbstractSession.VarId> opInputs, Set<AbstractSession.VarId> allIterInputs, Set<String> constAndPhInputs, List<Listener> listeners, At at, MultiDataSet batch, Set<String> allReqVariables)

Uses of Pair in org.nd4j.common.collection

Methods in org.nd4j.common.collection that return Pair

Modifier and Type	Method and Description
Pair<K,T>	MultiDimensionalMap.Entry.getKey() Returns the key corresponding to this entry.

Methods in org.nd4j.common.collection 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.nd4j.common.collection 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.nd4j.common.collection 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).

Constructor parameters in org.nd4j.common.collection with type arguments of type Pair

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

Uses of Pair in org.nd4j.common.function

Methods in org.nd4j.common.function that return types with arguments of type Pair

Modifier and Type	Method and Description
static <K,V> Map<K,Pair<List<V>,List<V>>>	FunctionalUtils.cogroup(List<Pair<K,V>> left, List<Pair<K,V>> right) For each key in left and right, cogroup returns the list of values as a pair for each value present in left as well as right.
static <K,V> List<Pair<K,V>>	FunctionalUtils.mapToPair(Map<K,V> map) Convert a map with a set of entries of type K for key and V for value in to a list of Pair

Method parameters in org.nd4j.common.function with type arguments of type Pair

Modifier and Type	Method and Description
static <K,V> Map<K,Pair<List<V>,List<V>>>	FunctionalUtils.cogroup(List<Pair<K,V>> left, List<Pair<K,V>> right) For each key in left and right, cogroup returns the list of values as a pair for each value present in left as well as right.
static <K,V> Map<K,Pair<List<V>,List<V>>>	FunctionalUtils.cogroup(List<Pair<K,V>> left, List<Pair<K,V>> right) For each key in left and right, cogroup returns the list of values as a pair for each value present in left as well as right.
static <K,V> Map<K,List<V>>	FunctionalUtils.groupByKey(List<Pair<K,V>> listInput) Group the input pairs by the key of each pair.

Uses of Pair in org.nd4j.common.primitives

Methods in org.nd4j.common.primitives that return Pair

Modifier and Type	Method and Description
Pair<F,S>	CounterMap.argMax() This method returns pair of elements with a max value
static <T,E> Pair<T,E>	Pair.create(T key, E value)
static <T> Pair<T,T>	Pair.fromArray(T[] arr)
static <T,E> Pair<T,E>	Pair.makePair(T key, E value)
static <T,E> Pair<T,E>	Pair.of(T key, E value)
static <T,E> Pair<T,E>	Pair.pairOf(T key, E value)

Methods in org.nd4j.common.primitives that return types with arguments of type Pair

Modifier and Type	Method and Description
PriorityQueue<Pair<T,Double>>	Counter.asPriorityQueue()
PriorityQueue<Pair<T,Double>>	Counter.asReversedPriorityQueue()
Iterator<Pair<F,S>>	CounterMap.getIterator() This method returns Iterator of all first/second pairs stored in this counter

Methods in org.nd4j.common.primitives with parameters of type Pair

Modifier and Type	Method and Description
int	Counter.PairComparator.compare(Pair<T,Double> o1, Pair<T,Double> o2)
int	Counter.PairComparator.compare(Pair<T,Double> o1, Pair<T,Double> o2)
int	Counter.ReversedPairComparator.compare(Pair<T,Double> o1, Pair<T,Double> o2)
int	Counter.ReversedPairComparator.compare(Pair<T,Double> o1, Pair<T,Double> o2)

Uses of Pair in org.nd4j.evaluation

Methods in org.nd4j.evaluation that return Pair

Modifier and Type	Method and Description
static Pair<INDArray,INDArray>	EvaluationUtils.extractNonMaskedTimeSteps(INDArray labels, INDArray predicted, INDArray outputMask)

Uses of Pair in org.nd4j.evaluation.classification

Fields in org.nd4j.evaluation.classification 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.nd4j.graph.ui

Methods in org.nd4j.graph.ui that return Pair

Modifier and Type	Method and Description
protected Pair<Integer,com.google.flatbuffers.FlatBufferBuilder>	LogFileWriter.encodeStaticHeader(byte type) Encode the header as a UIStaticInfoRecord instance for the specific UIEventType

Methods in org.nd4j.graph.ui that return types with arguments of type Pair

Modifier and Type	Method and Description
List<Pair<UIEvent,com.google.flatbuffers.Table>>	LogFileWriter.readEvents() Read all of the events.
List<Pair<UIEvent,com.google.flatbuffers.Table>>	LogFileWriter.readEvents(long startOffset) Read all of the events starting at a specific file offset

Uses of Pair in org.nd4j.linalg.activations

Methods in org.nd4j.linalg.activations that return Pair

Modifier and Type	Method and Description
Pair<INDArray,INDArray>	IActivation.backprop(INDArray in, INDArray epsilon) Backpropagate the errors through the activation function, given input z and epsilon dL/da.

Uses of Pair in org.nd4j.linalg.activations.impl

Methods in org.nd4j.linalg.activations.impl that return Pair

Modifier and Type	Method and Description
Pair<INDArray,INDArray>	ActivationCube.backprop(@NonNull INDArray in, @NonNull INDArray epsilon)
Pair<INDArray,INDArray>	ActivationELU.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationGELU.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationHardSigmoid.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationHardTanH.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationIdentity.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationLReLU.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationMish.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationPReLU.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationRationalTanh.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationRectifiedTanh.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationReLU.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationReLU6.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationRReLU.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationSELU.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationSigmoid.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationSoftmax.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationSoftPlus.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationSoftSign.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationSwish.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationTanH.backprop(INDArray in, INDArray epsilon)
Pair<INDArray,INDArray>	ActivationThresholdedReLU.backprop(INDArray in, INDArray epsilon)

Uses of Pair in org.nd4j.linalg.api.ndarray

Methods in org.nd4j.linalg.api.ndarray that return Pair

Modifier and Type	Method and Description
Pair<DataBuffer,long[]>	BaseShapeInfoProvider.createShapeInformation(long[] shape, char order, DataType dataType) This method creates shapeInformation buffer, based on shape & order being passed in
Pair<DataBuffer,long[]>	ShapeInfoProvider.createShapeInformation(long[] shape, char order, DataType dataType) This method creates long shapeInformation buffer, based on shape & order being passed in
Pair<DataBuffer,long[]>	BaseShapeInfoProvider.createShapeInformation(long[] shape, DataType dataType) This method creates shapeInformation buffer, based on shape being passed in
Pair<DataBuffer,long[]>	ShapeInfoProvider.createShapeInformation(long[] shape, DataType dataType) This method creates long shapeInformation buffer, based on shape being passed in
Pair<DataBuffer,long[]>	BaseShapeInfoProvider.createShapeInformation(long[] shape, long[] stride, long elementWiseStride, char order, DataType dataType, boolean empty)
Pair<DataBuffer,long[]>	ShapeInfoProvider.createShapeInformation(long[] shape, long[] stride, long elementWiseStride, char order, DataType dataType, boolean empty) This method creates long shapeInformation buffer, based on detailed shape info being passed in
Pair<DataBuffer,long[]>	BaseShapeInfoProvider.createShapeInformation(long[] shape, long[] stride, long elementWiseStride, char order, long extras)
Pair<DataBuffer,long[]>	ShapeInfoProvider.createShapeInformation(long[] shape, long[] stride, long elementWiseStride, char order, long extras)

Uses of Pair in org.nd4j.linalg.api.ops

Methods in org.nd4j.linalg.api.ops that return Pair

Modifier and Type	Method and Description
Pair<Long,Long>	OpContext.getRngStates() This method returns RNG states, root first node second

Uses of Pair in org.nd4j.linalg.cache

Methods in org.nd4j.linalg.cache that return Pair

Modifier and Type	Method and Description
Pair<DataBuffer,DataBuffer>	TADManager.getTADOnlyShapeInfo(INDArray array, int... dimension) This method returns TAD shapeInfo and all offsets for specified tensor and dimensions.

Uses of Pair in org.nd4j.linalg.checkutil

Methods in org.nd4j.linalg.checkutil that return Pair

Modifier and Type	Method and Description
static Pair<INDArray,String>	NDArrayCreationUtil.getPermutedWithShape(char ordering, long rows, long cols, long seed, DataType dataType)
static Pair<INDArray,String>	NDArrayCreationUtil.getPermutedWithShape(long rows, long cols, long seed, DataType dataType)
static Pair<INDArray,String>	NDArrayCreationUtil.getReshapedWithShape(char ordering, long rows, long cols, long seed, DataType dataType)
static Pair<INDArray,String>	NDArrayCreationUtil.getReshapedWithShape(long rows, long cols, long seed, DataType dataType)
static Pair<INDArray,String>	NDArrayCreationUtil.getTransposedMatrixWithShape(char ordering, int rows, int cols, int seed, DataType dataType)
static Pair<INDArray,String>	NDArrayCreationUtil.getTransposedMatrixWithShape(long rows, long cols, long seed, DataType dataType)

Methods in org.nd4j.linalg.checkutil that return types with arguments of type Pair

Modifier and Type	Method and Description
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get3dPermutedWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get3dPermutedWithShape(long seed, long[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get3dReshapedWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get3dReshapedWithShape(long seed, long[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get3dSubArraysWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get3dSubArraysWithShape(long seed, long[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get3dTensorAlongDimensionWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get3dTensorAlongDimensionWithShape(long seed, long[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get4dPermutedWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get4dReshapedWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get4dSubArraysWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get4dTensorAlongDimensionWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get5dPermutedWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get5dReshapedWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get5dSubArraysWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get5dTensorAlongDimensionWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get6dPermutedWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get6dReshapedWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.get6dSubArraysWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getAll3dTestArraysWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getAll3dTestArraysWithShape(long seed, long[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getAll4dTestArraysWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getAll4dTestArraysWithShape(int seed, long[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getAll5dTestArraysWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getAll6dTestArraysWithShape(int seed, int[] shape, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getAllTestMatricesWithShape(char ordering, int rows, int cols, int seed, DataType dataType) Get an array of INDArrays (2d) all with the specified shape.
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getAllTestMatricesWithShape(long rows, long cols, long seed, DataType dataType) Get an array of INDArrays (2d) all with the specified shape.
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getSubMatricesWithShape(char ordering, long rows, long cols, long seed, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getSubMatricesWithShape(long rows, long cols, long seed, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getTensorAlongDimensionMatricesWithShape(char ordering, long rows, long cols, long seed, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getTensorAlongDimensionMatricesWithShape(long rows, long cols, long seed, DataType dataType)
static List<Pair<INDArray,String>>	NDArrayCreationUtil.getTestMatricesWithVaryingShapes(int rank, char order, DataType dataType) Test utility to sweep shapes given a rank Given a rank will generate random test matrices that will cover all cases of a shape with a '1' anywhere in the shape as well a shape with random ints that are not 0 or 1 eg. rank 2: 1,1; 1,2; 2,1; 2,2; 3,4 Motivated by TADs that often hit bugs when a "1" occurs as the size of a dimension

Uses of Pair in org.nd4j.linalg.cpu.nativecpu

Methods in org.nd4j.linalg.cpu.nativecpu that return Pair

Modifier and Type	Method and Description
Pair<DataBuffer,long[]>	DirectShapeInfoProvider.createShapeInformation(long[] shape, long[] stride, long elementWiseStride, char order, DataType dataType)
Pair<DataBuffer,long[]>	DirectShapeInfoProvider.createShapeInformation(long[] shape, long[] stride, long elementWiseStride, char order, long extras)
Pair<DataBuffer,DataBuffer>	CpuTADManager.getTADOnlyShapeInfo(INDArray array, int[] dimension)

Uses of Pair in org.nd4j.linalg.cpu.nativecpu.ops

Methods in org.nd4j.linalg.cpu.nativecpu.ops that return Pair

Modifier and Type	Method and Description
Pair<Long,Long>	CpuOpContext.getRngStates()

Uses of Pair in org.nd4j.linalg.dataset.api

Methods in org.nd4j.linalg.dataset.api that return Pair

Modifier and Type	Method and Description
static Pair<INDArray,INDArray>	DataSetUtil.merge2d(@NonNull INDArray[][] arrays, INDArray[][] masks, int inOutIdx) Merge the specified 2d arrays and masks.
static Pair<INDArray,INDArray>	DataSetUtil.merge2d(INDArray[] arrays, INDArray[] masks) Merge the specified 2d arrays and masks.
static Pair<INDArray,INDArray>	DataSetUtil.merge4d(INDArray[][] arrays, INDArray[][] masks, int inOutIdx) Merge the specified 4d arrays and masks.
static Pair<INDArray,INDArray>	DataSetUtil.merge4d(INDArray[] arrays, INDArray[] masks) Merge the specified 4d arrays and masks.
static Pair<INDArray[],INDArray[]>	DataSetUtil.mergeFeatures(@NonNull INDArray[][] featuresToMerge, INDArray[][] featureMasksToMerge) Merge all of the features arrays into one minibatch.
static Pair<INDArray,INDArray>	DataSetUtil.mergeFeatures(INDArray[][] featuresToMerge, INDArray[][] featureMasksToMerge, int inOutIdx) Extract out the specified column, and merge the specified features and mask arrays (i.e., concatenate the examples)
static Pair<INDArray,INDArray>	DataSetUtil.mergeFeatures(@NonNull INDArray[] featuresToMerge, INDArray[] featureMasksToMerge) Merge the specified features and mask arrays (i.e., concatenate the examples)
static Pair<INDArray,INDArray>	DataSetUtil.mergeLabels(@NonNull INDArray[][] labelsToMerge, INDArray[][] labelMasksToMerge, int inOutIdx) Extract out the specified column, and merge the specified label and label mask arrays (i.e., concatenate the examples)
static Pair<INDArray,INDArray>	DataSetUtil.mergeLabels(INDArray[] labelsToMerge, INDArray[] labelMasksToMerge) Merge the specified labels and label mask arrays (i.e., concatenate the examples)
static Pair<INDArray,INDArray>	DataSetUtil.mergeTimeSeries(INDArray[][] arrays, INDArray[][] masks, int inOutIdx) Merge the specified time series (3d) arrays and masks.
static Pair<INDArray,INDArray>	DataSetUtil.mergeTimeSeries(INDArray[] arrays, INDArray[] masks) Merge the specified time series (3d) arrays and masks.

Uses of Pair in org.nd4j.linalg.factory

Methods in org.nd4j.linalg.factory with parameters of type Pair

Modifier and Type	Method and Description
static INDArray	Nd4j.createArrayFromShapeBuffer(DataBuffer data, Pair<DataBuffer,long[]> shapeInfo) Create array based in data buffer and shape info,

Uses of Pair in org.nd4j.linalg.lossfunctions

Methods in org.nd4j.linalg.lossfunctions that return Pair

Modifier and Type	Method and Description
Pair<Double,INDArray>	ILossFunction.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average) Compute both the score (loss function value) and gradient.
Pair<Double,INDArray>	SameDiffLoss.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average) Compute both the score (loss function value) and gradient.

Uses of Pair in org.nd4j.linalg.lossfunctions.impl

Methods in org.nd4j.linalg.lossfunctions.impl that return Pair

Modifier and Type	Method and Description
Pair<Double,INDArray>	LossBinaryXENT.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossCosineProximity.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossFMeasure.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossHinge.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossKLD.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossL1.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossL2.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossMAPE.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossMCXENT.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossMixtureDensity.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossMSLE.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossMultiLabel.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossPoisson.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossSparseMCXENT.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossSquaredHinge.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)
Pair<Double,INDArray>	LossWasserstein.computeGradientAndScore(INDArray labels, INDArray preOutput, IActivation activationFn, INDArray mask, boolean average)

Uses of Pair in org.nd4j.parameterserver.distributed

Methods in org.nd4j.parameterserver.distributed that return Pair

Modifier and Type	Method and Description
protected Pair<NodeRole,String>	VoidParameterServer.getRole(@NonNull VoidConfiguration voidConfiguration, @NonNull Collection<String> localIPs) Deprecated. This method checks for designated role, according to local IP addresses and configuration passed into method

Uses of Pair in org.nd4j.parameterserver.distributed.v2

Methods in org.nd4j.parameterserver.distributed.v2 that return Pair

Modifier and Type	Method and Description
Pair<Integer,Integer>	ModelParameterServer.getStartPosition() This method returns pair of integers: iteration number and epoch number

Uses of Pair in org.nd4j.remote.grpc

Methods in org.nd4j.remote.grpc with parameters of type Pair

Modifier and Type	Method and Description
INDArray[]	GraphInferenceGrpcClient.output(long graphId, Pair<String,INDArray>... inputs) This method sends inference request to the GraphServer instance, and returns result as array of INDArrays
INDArray[]	GraphInferenceGrpcClient.output(Pair<String,INDArray>... inputs) This method sends inference request to the GraphServer instance, and returns result as array of INDArrays PLEASE NOTE: This call will be routed to default graph with id 0

Uses of Pair in org.nd4j.serde.binary

Methods in org.nd4j.serde.binary that return Pair

Modifier and Type	Method and Description
protected static Pair<INDArray,ByteBuffer>	BinarySerde.toArrayAndByteBuffer(ByteBuffer buffer, int offset) Create an ndarray and existing bytebuffer

Uses of Pair in org.nd4j.systeminfo

Methods in org.nd4j.systeminfo that return Pair

Modifier and Type	Method and Description
static Pair<String,String>	SystemInfo.inferVersion()