| Modifier and Type | Method and Description |
|---|---|
INDArray |
SequenceLearningAlgorithm.inferSequence(Sequence<T> sequence,
long nextRandom,
double learningRate,
double minLearningRate,
int iterations)
This method does training on previously unseen paragraph, and returns inferred vector
|
double |
ElementsLearningAlgorithm.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate)
This method does training over the sequence of elements passed into it
|
double |
SequenceLearningAlgorithm.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate,
BatchSequences<T> batchSequences)
This method does training over the sequence of elements passed into it
|
double |
ElementsLearningAlgorithm.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate,
BatchSequences<T> batchSequences) |
| Modifier and Type | Method and Description |
|---|---|
Sequence<T> |
SkipGram.applySubsampling(Sequence<T> sequence,
AtomicLong nextRandom) |
Sequence<T> |
CBOW.applySubsampling(Sequence<T> sequence,
AtomicLong nextRandom) |
| Modifier and Type | Method and Description |
|---|---|
Sequence<T> |
SkipGram.applySubsampling(Sequence<T> sequence,
AtomicLong nextRandom) |
Sequence<T> |
CBOW.applySubsampling(Sequence<T> sequence,
AtomicLong nextRandom) |
double |
SkipGram.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate)
Learns sequence using SkipGram algorithm
|
double |
GloVe.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate)
Learns sequence using GloVe algorithm
|
double |
CBOW.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate) |
double |
SkipGram.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate,
BatchSequences<T> batchSequences) |
double |
GloVe.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate,
BatchSequences<T> batchSequences) |
double |
CBOW.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate,
BatchSequences<T> batchSequences) |
| Modifier and Type | Method and Description |
|---|---|
protected void |
DBOW.dbow(int i,
Sequence<T> sequence,
int b,
AtomicLong nextRandom,
double alpha,
boolean isInference,
INDArray inferenceVector,
BatchSequences<T> batchSequences) |
void |
DM.dm(int i,
Sequence<T> sequence,
int b,
AtomicLong nextRandom,
double alpha,
List<T> labels,
boolean isInference,
INDArray inferenceVector,
BatchSequences<T> batchSequences) |
INDArray |
DM.inferSequence(Sequence<T> sequence,
long nr,
double learningRate,
double minLearningRate,
int iterations)
This method does training on previously unseen paragraph, and returns inferred vector
|
INDArray |
DBOW.inferSequence(Sequence<T> sequence,
long nextRandom,
double learningRate,
double minLearningRate,
int iterations)
This method does training on previously unseen paragraph, and returns inferred vector
|
double |
DM.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate,
BatchSequences<T> batchSequences) |
double |
DBOW.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate,
BatchSequences<T> batchSequences) |
| Modifier and Type | Method and Description |
|---|---|
Sequence<T> |
SequenceVectors.AsyncSequencer.nextSentence() |
| Modifier and Type | Method and Description |
|---|---|
protected void |
SequenceVectors.trainSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double alpha) |
| Modifier and Type | Method and Description |
|---|---|
Sequence<T> |
GraphWalker.next()
This method returns next walk sequence from this graph
|
| Modifier and Type | Method and Description |
|---|---|
Sequence<T> |
WeightedWalker.next()
This method returns next walk sequence from this graph
|
Sequence<T> |
RandomWalker.next()
This method returns next walk sequence from this graph
|
Sequence<T> |
PopularityWalker.next()
This method returns next walk sequence from this graph
|
Sequence<V> |
NearestVertexWalker.next() |
protected Sequence<V> |
NearestVertexWalker.walk(Vertex<V> node,
int cDepth) |
| Modifier and Type | Method and Description |
|---|---|
Sequence<T> |
SequenceIterator.nextSequence() |
| Modifier and Type | Method and Description |
|---|---|
Sequence<T> |
SynchronizedSequenceIterator.nextSequence()
Returns next sequence from data source
|
Sequence<T> |
FilteredSequenceIterator.nextSequence()
Returns filtered sequence, that contains sequence elements from vocabulary only.
|
Sequence<T> |
AbstractSequenceIterator.nextSequence()
Returns next sequence out of iterator
|
| Constructor and Description |
|---|
AbstractSequenceIterator(Iterable<Sequence<T>> iterable) |
Builder(Iterable<Sequence<T>> iterable)
Builds AbstractSequenceIterator on top of Iterable object
|
| Modifier and Type | Method and Description |
|---|---|
Sequence<T> |
SequenceTransformer.transformToSequence(V object)
This is generic method for transformation data from any format to Sequence of SequenceElement.
|
| Modifier and Type | Method and Description |
|---|---|
Sequence<VocabWord> |
SentenceTransformer.transformToSequence(String object) |
| Modifier and Type | Method and Description |
|---|---|
Iterator<Sequence<VocabWord>> |
SentenceTransformer.iterator() |
Iterator<Sequence<T>> |
GraphTransformer.iterator() |
| Modifier and Type | Field and Description |
|---|---|
protected BlockingQueue<Future<Sequence<VocabWord>>> |
ParallelTransformerIterator.buffer |
| Modifier and Type | Method and Description |
|---|---|
Sequence<VocabWord> |
ParallelTransformerIterator.next() |
Sequence<VocabWord> |
BasicTransformerIterator.next() |
| Modifier and Type | Method and Description |
|---|---|
void |
VocabConstructor.processDocument(AbstractCache<T> targetVocab,
Sequence<T> document,
AtomicLong finalCounter,
AtomicLong loopCounter) |
| Constructor and Description |
|---|
VocabRunnable(AbstractCache<T> targetVocab,
Sequence<T> sequence,
AtomicLong finalCounter,
AtomicLong loopCounter) |
| Modifier and Type | Method and Description |
|---|---|
Sequence<VocabWord> |
DocumentSequenceConvertFunction.call(LabelledDocument document) |
Sequence<VocabWord> |
KeySequenceConvertFunction.call(scala.Tuple2<String,String> pair) |
| Modifier and Type | Method and Description |
|---|---|
void |
SparkSequenceVectors.fitSequences(org.apache.spark.api.java.JavaRDD<Sequence<T>> corpus)
Base training entry point
|
| Modifier and Type | Method and Description |
|---|---|
Sequence<T> |
ListSequenceConvertFunction.call(List<T> ts) |
Sequence<VocabWord> |
TokenizerFunction.call(String s) |
| Modifier and Type | Method and Description |
|---|---|
Pair<Sequence<T>,Long> |
ExtraCountFunction.call(Sequence<T> sequence) |
Pair<Sequence<T>,Long> |
CountFunction.call(Sequence<T> sequence) |
| Modifier and Type | Method and Description |
|---|---|
Iterator<T> |
VocabRddFunctionFlat.call(Sequence<T> sequence) |
void |
TrainingFunction.call(Sequence<T> sequence) |
Pair<Sequence<T>,Long> |
ExtraCountFunction.call(Sequence<T> sequence) |
Pair<Sequence<T>,Long> |
CountFunction.call(Sequence<T> sequence) |
| Modifier and Type | Method and Description |
|---|---|
void |
PartitionTrainingFunction.call(Iterator<Sequence<T>> sequenceIterator) |
protected void |
PartitionTrainingFunction.trainAllAtOnce(List<Sequence<ShallowSequenceElement>> sequences) |
| Modifier and Type | Method and Description |
|---|---|
Frame<? extends TrainingMessage> |
SparkElementsLearningAlgorithm.frameSequence(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
double learningRate) |
| Modifier and Type | Method and Description |
|---|---|
static Sequence<ShallowSequenceElement> |
BaseSparkLearningAlgorithm.applySubsampling(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
long totalElementsCount,
double prob) |
| Modifier and Type | Method and Description |
|---|---|
static Sequence<ShallowSequenceElement> |
BaseSparkLearningAlgorithm.applySubsampling(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
long totalElementsCount,
double prob) |
Frame<? extends TrainingMessage> |
SparkSkipGram.frameSequence(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
double learningRate) |
Frame<? extends TrainingMessage> |
SparkCBOW.frameSequence(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
double learningRate) |
double |
BaseSparkLearningAlgorithm.learnSequence(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
double learningRate) |
double |
SparkSkipGram.learnSequence(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
double learningRate,
BatchSequences<ShallowSequenceElement> batchSequences) |
double |
SparkCBOW.learnSequence(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
double learningRate,
BatchSequences<ShallowSequenceElement> batchSequences) |
| Modifier and Type | Method and Description |
|---|---|
Frame<? extends TrainingMessage> |
SparkDM.frameSequence(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
double learningRate) |
Frame<? extends TrainingMessage> |
SparkDBOW.frameSequence(Sequence<ShallowSequenceElement> sequence,
AtomicLong nextRandom,
double learningRate) |
INDArray |
BaseSparkSequenceLearningAlgorithm.inferSequence(Sequence<ShallowSequenceElement> sequence,
long nextRandom,
double learningRate,
double minLearningRate,
int iterations) |
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