SpanModel

Instance Constructors

new SpanModel(featurizer: RefinedFeaturizer[L, W, Feature], featureIndex: Index[Feature], annotator: (BinarizedTree[L], IndexedSeq[W]) ⇒ BinarizedTree[IndexedSeq[L2]], constrainer: Factory[L, W], topology: RuleTopology[L], lexicon: Lexicon[L, W], refinedGrammar: RuleTopology[L2], refinements: GrammarRefinements[L, L2], initialFeatureVal: (Feature) ⇒ Option[Double] = _ => None)

Type Members

type ExpectedCounts = StandardExpectedCounts[Feature]

Definition Classes
Model → Model
type Inference = LatentParserInference[L, L2, W]

Definition Classes
SpanModel → ParserModel → Model
type Marginal = ParseMarginal[L, W]

Definition Classes
ParserModel → Model
type Scorer = GrammarAnchoring[L, W]

Definition Classes
ParserModel → Model

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def accumulateCounts(inf: Inference, s: Scorer, d: TreeInstance[L, W], m: Marginal, accum: ExpectedCounts, scale: Double): Unit

Definition Classes
SpanModel → Model
final def accumulateCounts(inf: Inference, d: TreeInstance[L, W], accum: ExpectedCounts, scale: Double): Unit

Definition Classes
Model
val annotator: (BinarizedTree[L], IndexedSeq[W]) ⇒ BinarizedTree[IndexedSeq[L2]]
final def asInstanceOf[T0]: T0

Definition Classes
Any
def cacheFeatureWeights(weights: DenseVector[Double], suffix: String = ""): Unit

Caches the weights using the cache broker.
Caches the weights using the cache broker.

Definition Classes
Model
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate() @throws( ... )
val constrainer: Factory[L, W]

Definition Classes
SpanModel → ParserExtractable
def emptyCounts: StandardExpectedCounts[Feature]

Definition Classes
Model → Model
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def expectedCounts(inf: Inference, d: TreeInstance[L, W], scale: Double = 1.0): ExpectedCounts

Definition Classes
Model
def expectedCountsToObjective(ecounts: ExpectedCounts): (Double, DenseVector[Double])

Definition Classes
Model → Model
def extractParser(weights: DenseVector[Double])(implicit deb: Debinarizer[L]): Parser[L, W]

Definition Classes
ParserModel → ParserExtractable
val featureIndex: Index[Feature]

Models have features, and this defines the mapping from indices in the weight vector to features.
Models have features, and this defines the mapping from indices in the weight vector to features.

Definition Classes
SpanModel → Model
val featurizer: RefinedFeaturizer[L, W, Feature]
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
Annotations
@HotSpotIntrinsicCandidate()
def hashCode(): Int

Definition Classes
AnyRef → Any
Annotations
@HotSpotIntrinsicCandidate()
def inferenceFromWeights(weights: DenseVector[Double]): LatentParserInference[L, L2, W]

Definition Classes
SpanModel → Model
def initialValueForFeature(f: Feature): Double

Definition Classes
SpanModel → Model
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
val lexicon: Lexicon[L, W]

Definition Classes
SpanModel → ParserExtractable
def logger: LazyLogger

Attributes
protected
Definition Classes
SerializableLogging
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate()
def numFeatures: Int

Definition Classes
Model
def readCachedFeatureWeights(suffix: String = ""): Option[DenseVector[Double]]

just saves feature weights to disk as a serialized counter.
just saves feature weights to disk as a serialized counter. The file is prefix.ser.gz

Definition Classes
Model
val refinedGrammar: RuleTopology[L2]
val refinements: GrammarRefinements[L, L2]
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
val topology: RuleTopology[L]

Definition Classes
SpanModel → ParserExtractable
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
def weightsCacheName: String

Attributes
protected
Definition Classes
Model

Deprecated Value Members

def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@Deprecated @deprecated @throws( classOf[java.lang.Throwable] )
Deprecated
(Since version ) see corresponding Javadoc for more information.

Related Doc: package models

class SpanModel[L, L2, W] extends ParserModel[L, W] with Serializable

Instance Constructors

Type Members

type ExpectedCounts = StandardExpectedCounts[Feature]

type Inference = LatentParserInference[L, L2, W]

type Marginal = ParseMarginal[L, W]

type Scorer = GrammarAnchoring[L, W]

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def accumulateCounts(inf: Inference, s: Scorer, d: TreeInstance[L, W], m: Marginal, accum: ExpectedCounts, scale: Double): Unit

final def accumulateCounts(inf: Inference, d: TreeInstance[L, W], accum: ExpectedCounts, scale: Double): Unit

val annotator: (BinarizedTree[L], IndexedSeq[W]) ⇒ BinarizedTree[IndexedSeq[L2]]

final def asInstanceOf[T0]: T0

def cacheFeatureWeights(weights: DenseVector[Double], suffix: String = ""): Unit

def clone(): AnyRef

val constrainer: Factory[L, W]

def emptyCounts: StandardExpectedCounts[Feature]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

final def expectedCounts(inf: Inference, d: TreeInstance[L, W], scale: Double = 1.0): ExpectedCounts

def expectedCountsToObjective(ecounts: ExpectedCounts): (Double, DenseVector[Double])

def extractParser(weights: DenseVector[Double])(implicit deb: Debinarizer[L]): Parser[L, W]

val featureIndex: Index[Feature]

val featurizer: RefinedFeaturizer[L, W, Feature]

final def getClass(): Class[_]

def hashCode(): Int

def inferenceFromWeights(weights: DenseVector[Double]): LatentParserInference[L, L2, W]

def initialValueForFeature(f: Feature): Double

final def isInstanceOf[T0]: Boolean

val lexicon: Lexicon[L, W]

def logger: LazyLogger

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def numFeatures: Int

def readCachedFeatureWeights(suffix: String = ""): Option[DenseVector[Double]]

val refinedGrammar: RuleTopology[L2]

val refinements: GrammarRefinements[L, L2]

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

val topology: RuleTopology[L]

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

final def wait(): Unit

def weightsCacheName: String

Deprecated Value Members

def finalize(): Unit

Inherited from ParserModel[L, W]

Inherited from ParserExtractable[L, W]

Inherited from Model[TreeInstance[L, W]]

Inherited from Model[TreeInstance[L, W]]

Inherited from SerializableLogging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped