Modifier and Type | Method and Description |
---|---|
org.nd4j.linalg.api.ndarray.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)
This method does training over the sequence of elements passed into it
|
Modifier and Type | Method and Description |
---|---|
Sequence<T> |
CBOW.applySubsampling(Sequence<T> sequence,
AtomicLong nextRandom) |
Sequence<T> |
SkipGram.applySubsampling(Sequence<T> sequence,
AtomicLong nextRandom) |
Modifier and Type | Method and Description |
---|---|
Sequence<T> |
CBOW.applySubsampling(Sequence<T> sequence,
AtomicLong nextRandom) |
Sequence<T> |
SkipGram.applySubsampling(Sequence<T> sequence,
AtomicLong nextRandom) |
double |
CBOW.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate) |
double |
GloVe.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate)
Learns sequence using GloVe algorithm
|
double |
SkipGram.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate)
Learns sequence using SkipGram algorithm
|
Modifier and Type | Method and Description |
---|---|
protected void |
DBOW.dbow(int i,
Sequence<T> sequence,
int b,
AtomicLong nextRandom,
double alpha,
boolean isInference,
org.nd4j.linalg.api.ndarray.INDArray inferenceVector) |
void |
DM.dm(int i,
Sequence<T> sequence,
int b,
AtomicLong nextRandom,
double alpha,
List<T> labels,
boolean isInference,
org.nd4j.linalg.api.ndarray.INDArray inferenceVector) |
org.nd4j.linalg.api.ndarray.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
|
org.nd4j.linalg.api.ndarray.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
|
double |
DBOW.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate) |
double |
DM.learnSequence(Sequence<T> sequence,
AtomicLong nextRandom,
double learningRate) |
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<V> |
NearestVertexWalker.next() |
Sequence<T> |
PopularityWalker.next()
This method returns next walk sequence from this graph
|
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
|
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> |
FilteredSequenceIterator.nextSequence()
Returns filtered sequence, that contains sequence elements from vocabulary only.
|
Sequence<T> |
AbstractSequenceIterator.nextSequence()
Returns next sequence out of iterator
|
Sequence<T> |
SynchronizedSequenceIterator.nextSequence()
Returns next sequence from data source
|
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<Sequence<VocabWord>> |
ParallelTransformerIterator.buffer |
Modifier and Type | Method and Description |
---|---|
Sequence<VocabWord> |
ParallelTransformerIterator.next() |
Sequence<VocabWord> |
BasicTransformerIterator.next() |
Constructor and Description |
---|
VocabRunnable(AbstractCache<T> targetVocab,
Sequence<T> sequence,
AtomicLong finalCounter,
AtomicLong loopCounter) |
Copyright © 2018. All rights reserved.