Class

com.johnsnowlabs.ml.tensorflow

TensorflowMarian

Related Doc: package tensorflow

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class TensorflowMarian extends Serializable

MarianTransformer: Fast Neural Machine Translation

MarianTransformer uses models trained by MarianNMT.

Marian is an efficient, free Neural Machine Translation framework written in pure C++ with minimal dependencies. It is mainly being developed by the Microsoft Translator team. Many academic (most notably the University of Edinburgh and in the past the Adam Mickiewicz University in Poznań) and commercial contributors help with its development.

It is currently the engine behind the Microsoft Translator Neural Machine Translation services and being deployed by many companies, organizations and research projects (see below for an incomplete list).

Sources : MarianNMT https://marian-nmt.github.io/ Marian: Fast Neural Machine Translation in C++ https://www.aclweb.org/anthology/P18-4020/

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Instance Constructors

  1. new TensorflowMarian(tensorflow: TensorflowWrapper, sppSrc: SentencePieceWrapper, sppTrg: SentencePieceWrapper, configProtoBytes: Option[Array[Byte]] = None)

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    tensorflow

    LanguageDetectorDL Model wrapper with TensorFlow Wrapper

    sppSrc

    Contains the vocabulary for the target language.

    sppTrg

    Contains the vocabulary for the source language

    configProtoBytes

    Configuration for TensorFlow session

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 clone(): AnyRef

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    Attributes
    protected[java.lang]
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    @throws( ... )

  6. def decode(sentences: Array[Array[Long]], vocabsArray: Array[String]): Seq[String]

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  7. def encode(sentences: Seq[Annotation], normalizer: MosesPunctNormalizer, maxSeqLength: Int, vocabsArray: Array[String], langId: Long, unknownTokenId: Long, eosTokenId: Long): Seq[Array[Long]]

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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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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )

  11. def generateSeq2Seq(sentences: Seq[Annotation], batchSize: Int = 1, maxInputLength: Int, maxOutputLength: Int, vocabs: Array[String], langId: String): Array[Annotation]

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

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  13. def hashCode(): Int

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  14. final def isInstanceOf[T0]: Boolean

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

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. def process(batch: Seq[Array[Long]], maxOutputLength: Int, paddingTokenId: Long, eosTokenId: Long, vocabSize: Int): Array[Array[Long]]

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  19. val sppSrc: SentencePieceWrapper

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    Contains the vocabulary for the target language.

  20. val sppTrg: SentencePieceWrapper

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    Contains the vocabulary for the source language

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

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  22. val tensorflow: TensorflowWrapper

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    LanguageDetectorDL Model wrapper with TensorFlow Wrapper

  23. def toString(): String

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  24. final def wait(): Unit

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

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

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