Metal

Value Members

1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. final def asInstanceOf[T0]: T0

   

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5. def batchBackprop(batchLosses: ExpressionVector, trainer: SafeTrainer): Float

   

6. def chooseOptimalPreds(predsWithScores: IndexedSeq[IndexedSeq[(String, Float)]], goldLabels: IndexedSeq[String], topK: Int): IndexedSeq[String]

   

   Ceiling method that chooses the gold dependency for each modifier from the top K predictions

7. def clone(): AnyRef

   

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8. final def eq(arg0: AnyRef): Boolean

   

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9. def equals(arg0: Any): Boolean

   

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10. def evaluate(taskId: Int, taskName: String, sentences: Array[Array[Row]], name: String, epoch: Int): (Double, Double, Double, Double)

    

    Computes accuracy/P/R/F1 for the evaluation dataset of the given task Where possible, it also saves CoNLL-2003 compatible files of the output

11. def evaluate(taskId: Int, taskName: String, sentences: Array[Array[Row]]): (Double, Double, Double, Double)

    

12. def evaluate(taskId: Int, taskName: String, sentences: Array[Array[Row]], epoch: Int): (Double, Double, Double, Double)

    

13. def finalize(): Unit

    

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14. final def getClass(): Class[_]

    

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15. def hashCode(): Int

    

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16. def initialize(): Array[Layers]

    

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17. final def isInstanceOf[T0]: Boolean

    

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18. def mkVocabularies(): (Array[Counter[String]], Array[Counter[String]])

    

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19. lazy val model: IndexedSeq[Layers]

    

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20. final def ne(arg0: AnyRef): Boolean

    

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21. final def notify(): Unit

    

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22. final def notifyAll(): Unit

    

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23. val parameters: ParameterCollection

    

24. def parse(sentence: AnnotatedSentence, constEmbeddings: ConstEmbeddingParameters): IndexedSeq[(Int, String)]

    

    Custom method for the parsing algorithm

    Custom method for the parsing algorithm

    sentence

    Input sentence

    constEmbeddings

    Constant embeddings for this sentence

    returns

    Tuple of (head, label) for each word in the sentence

25. def parseWithEisner(sentence: AnnotatedSentence, constEmbeddings: ConstEmbeddingParameters, topK: Int, lambda: Float): IndexedSeq[(Int, String)]

    

26. def predict(taskId: Int, sentence: AnnotatedSentence, modHeadPairsOpt: Option[IndexedSeq[ModifierHeadPair]], constEmbeddings: ConstEmbeddingParameters): IndexedSeq[String]

    

27. def predictJointly(sentence: AnnotatedSentence, constEmbeddings: ConstEmbeddingParameters): IndexedSeq[IndexedSeq[String]]

    

28. def predictWithScores(taskId: Int, sentence: AnnotatedSentence, modHeadPairsOpt: Option[IndexedSeq[ModifierHeadPair]], constEmbeddings: ConstEmbeddingParameters, applySoftmax: Boolean = true): IndexedSeq[IndexedSeq[(String, Float)]]

    

29. def save(baseFilename: String): Unit

    

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

    

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31. def taskManager: TaskManager

    

32. val taskManagerOpt: Option[TaskManager]

    

33. def test(): Unit

    

34. def toString(): String

    

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35. def train(modelNamePrefix: String): Unit

    

36. final def wait(): Unit

    

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

    

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38. final def wait(arg0: Long): Unit

    

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