TensorflowNer

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. val batchSize: Int

   

6. def calcStat(correct: Int, predicted: Int, predictedCorrect: Int): (Float, Float, Float)

   

7. def clone(): AnyRef

   

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8. def doSlice[T](dataset: TraversableOnce[T], getLen: (T) ⇒ Int, batchSize: Int = 32)(implicit arg0: ClassTag[T]): Iterator[Array[T]]

   

9. val encoder: NerDatasetEncoder

   

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

    

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11. def equals(arg0: Any): Boolean

    

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12. def finalize(): Unit

    

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

    

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14. def getLogName: String

    

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    TensorflowNer → Logging

15. def getPiecesTags(tokenTags: Array[TextSentenceLabels], sentences: Array[WordpieceEmbeddingsSentence]): Array[Array[String]]

    

16. def getPiecesTags(tokenTags: TextSentenceLabels, sentence: WordpieceEmbeddingsSentence): Array[String]

    

17. def hashCode(): Int

    

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18. final def isInstanceOf[T0]: Boolean

    

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19. def log(value: ⇒ String, minLevel: Level): Unit

    

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    Logging

20. val logger: Logger

    

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    Logging

21. def measure(labeled: Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)], log: (String) ⇒ Unit, extended: Boolean = false, nErrorsToPrint: Int = 0, batchSize: Int = 20): Unit

    

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

    

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23. final def notify(): Unit

    

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24. final def notifyAll(): Unit

    

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25. def predict(dataset: Array[WordpieceEmbeddingsSentence]): Array[Array[String]]

    

26. def slice(dataset: TraversableOnce[(TextSentenceLabels, WordpieceEmbeddingsSentence)], batchSize: Int = 32): Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]]

    

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

    

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28. def tagsForTokens(labels: Array[Array[String]], pieces: Array[WordpieceEmbeddingsSentence]): Array[Array[String]]

    

29. def tagsForTokens(labels: Array[String], pieces: WordpieceEmbeddingsSentence): Array[String]

    

30. val tensorflow: TensorflowWrapper

    

31. def toString(): String

    

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32. def train(trainDataset: Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)], lr: Float, po: Float, batchSize: Int, dropout: Float, startEpoch: Int, endEpoch: Int, validation: Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)] = Array.empty): Unit

    

33. val verboseLevel: nlp.annotators.ner.Verbose.Value

    

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    TensorflowNer → Logging

34. final def wait(): Unit

    

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

    

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

    

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