trait
NeuralStochasticCrfScoring extends PotentialScoring
Type Members
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type
Matrix = Array[Array[Double]]
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type
Tensor = Array[Matrix]
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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def
computeGateActivations(lambdas: Array[Double], acts: Array[Double], wActs: Array[Double], numFs: Int, gateIdx: Int, nls: Int, nGates: Int, nNfs: Int, inst_features: Array[Array[Feature]]): Unit
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def
computeScores(ri: Matrix, mi: Tensor, lambdas: Array[Double], acts: Array[Double], wActs: Array[Double], numFs: Int, gateIdx: Int, nls: Int, nGates: Int, nNfs: Int, inst_features: Array[Array[Feature]], takeExp: Boolean): Unit
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final
def
computeScores(ri: Matrix, mi: Tensor, inst_features: Array[Array[Feature]], takeExp: Boolean, nls: Int, lambdas: Array[Double]): Unit
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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final
def
matrixMult(mat: Matrix, vec: Array[Double], rvec: Array[Double], alpha: Double, beta: Double, trans: Boolean): Unit
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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final
def
setMatrix(m: Matrix, v: Double = 0.0): Unit
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final
def
setTensor(t: Tensor, v: Double = 0.0): Unit
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Inherited from AnyRef
Inherited from Any
