com.intel.analytics.bigdl.example.udfpredictor

Utils

object Utils

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Type Members

  1. type Model = AbstractModule[Activity, Activity, Float]

  2. case class Sample(filename: String, text: String) extends Product with Serializable

  3. type SampleShape = Array[Int]

  4. type TFP = TextClassificationUDFParams

  5. type Word2Index = Map[String, Int]

  6. type Word2Meta = Map[String, WordMeta]

  7. type Word2Vec = Map[Float, Array[Float]]

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

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  10. def finalize(): Unit

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  11. def genUdf(sc: SparkContext, model: Model, sampleShape: Array[Int], word2Index: Word2Index, word2Vec: Word2Vec)(implicit ev: TensorNumeric[Float]): (String) ⇒ Int

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

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  13. def getModel(sc: SparkContext, param: TFP): (Model, Option[Word2Meta], Option[Word2Vec], SampleShape)

  14. def getResourcePath(resource: String): String

  15. def getTextClassifier(param: TextClassificationUDFParams): TextClassifier

  16. def getWord2Vec(word2Index: Map[String, Int]): Map[Float, Array[Float]]

  17. def hashCode(): Int

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  18. final def isInstanceOf[T0]: Boolean

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  19. def loadTestData(testDir: String): IndexedSeq[Sample]

  20. val localParser: OptionParser[TextClassificationUDFParams]

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

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  22. final def notify(): Unit

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  23. final def notifyAll(): Unit

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

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  25. def toString(): String

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  26. final def wait(): Unit

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

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

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