class TensorflowLD extends Serializable

Language Identification and Detection by using CNNs and RNNs architectures in TensowrFlow

The models are trained on large datasets such as Wikipedia and Tatoeba The output is a language code in Wiki Code style: https://en.wikipedia.org/wiki/List_of_Wikipedias

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Instance Constructors

  1. new TensorflowLD(tensorflow: TensorflowWrapper, configProtoBytes: Option[Array[Byte]] = None, orderedLanguages: ListMap[String, Int], orderedAlphabets: ListMap[String, Int])

    tensorflow

    LanguageDetectorDL Model wrapper with TensorFlow Wrapper

    configProtoBytes

    Configuration for TensorFlow session

    orderedLanguages

    ordered ListMap of language codes detectable by this trained model

    orderedAlphabets

    ordered ListMap of alphabets to be used to encode the inputs

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 cleanText(docs: List[String]): List[String]
  6. def clone(): AnyRef
    Attributes
    protected[lang]
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    @throws( ... ) @native()
  7. def encode(docs: Seq[Sentence]): Array[Array[Float]]
  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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    protected[lang]
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    @throws( classOf[java.lang.Throwable] )
  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(documents: Seq[Sentence], threshold: Float = 0.01f, thresholdLabel: String = "unk", coalesceSentences: Boolean = false): Array[Annotation]
  18. final def synchronized[T0](arg0: ⇒ T0): T0
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  19. def tag(inputs: Array[Array[Float]], inputSize: Int, outputSize: Int): Array[Array[Float]]
  20. val tensorflow: TensorflowWrapper
  21. def toString(): String
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  22. final def wait(): Unit
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  23. final def wait(arg0: Long, arg1: Int): Unit
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  24. final def wait(arg0: Long): Unit
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