c

com.johnsnowlabs.ml.tensorflow

TensorflowAlbertClassification

class TensorflowAlbertClassification extends Serializable

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Instance Constructors

  1. new TensorflowAlbertClassification(tensorflowWrapper: TensorflowWrapper, spp: SentencePieceWrapper, configProtoBytes: Option[Array[Byte]] = None, tags: Map[String, Int], signatures: Option[Map[String, String]] = None)

    tensorflowWrapper

    ALBERT Model wrapper with TensorFlow Wrapper

    spp

    ALBERT SentencePiece model with SentencePieceWrapper

    configProtoBytes

    Configuration for TensorFlow session

    tags

    labels which model was trained with in order

    signatures

    TF v2 signatures in Spark NLP

Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
    Definition Classes
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  3. final def ==(arg0: Any): Boolean
    Definition Classes
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  4. val _tfAlbertSignatures: Map[String, String]
  5. final def asInstanceOf[T0]: T0
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  6. def calcluateSoftmax(scores: Array[Float]): Array[Float]
  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 finalize(): Unit
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  11. final def getClass(): Class[_]
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    @native()
  12. def hashCode(): Int
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  13. final def isInstanceOf[T0]: Boolean
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  14. final def ne(arg0: AnyRef): Boolean
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  15. final def notify(): Unit
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    @native()
  16. final def notifyAll(): Unit
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    @native()
  17. def predict(tokenizedSentences: Seq[TokenizedSentence], batchSize: Int, maxSentenceLength: Int, caseSensitive: Boolean): Seq[Annotation]
  18. def prepareBatchInputs(sentences: Seq[(WordpieceTokenizedSentence, Int)], maxSequenceLength: Int): Seq[Array[Int]]

    Encode the input sequence to indexes IDs adding padding where necessary

  19. val spp: SentencePieceWrapper
  20. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
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  21. def tag(batch: Seq[Array[Int]]): Seq[Array[Array[Float]]]
  22. val tensorflowWrapper: TensorflowWrapper
  23. def toString(): String
    Definition Classes
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  24. def tokenizeWithAlignment(sentences: Seq[TokenizedSentence], maxSeqLength: Int, caseSensitive: Boolean): Seq[WordpieceTokenizedSentence]
  25. final def wait(): Unit
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  26. final def wait(arg0: Long, arg1: Int): Unit
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  27. final def wait(arg0: Long): Unit
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