Class

com.johnsnowlabs.ml.tensorflow

TensorflowAssertion

Related Doc: package tensorflow

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class TensorflowAssertion extends Logging

Created by jose on 15/03/18.

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  1. TensorflowAssertion
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Instance Constructors

  1. new TensorflowAssertion(tensorflow: TensorflowWrapper, encoder: AssertionDatasetEncoder, batchSize: Int, verboseLevel: nlp.annotators.ner.Verbose.Value)

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Value Members

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

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    AnyRef → Any
  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

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  6. def calcStat(tp: Int, fp: Int, fn: Int): (Float, Float, Float)

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  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. val encoder: AssertionDatasetEncoder

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

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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  12. final def getClass(): Class[_]

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  13. def getLogName: String

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    Definition Classes
    Logging
  14. def getPiecesTags(tokenTags: Array[TextSentenceLabels], sentences: Array[WordpieceEmbeddingsSentence]): Array[Array[String]]

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

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  16. def hashCode(): Int

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  17. final def isInstanceOf[T0]: Boolean

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

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    Attributes
    protected
    Definition Classes
    Logging
  19. val logger: Logger

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    Attributes
    protected
    Definition Classes
    Logging
  20. def measure(labeled: Array[(WordpieceEmbeddingsSentence, AssertionAnnotationWithLabel)], batchSize: Int = 100, outputLogsPath: String, embeddingsDim: Int, maxLen: Int, configProtoBytes: Option[Array[Byte]] = None, enableOutputLogs: Boolean = false, extended: Boolean = true, uuid: String = Identifiable.randomUID("annotator")): Unit

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  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. def outputLog(value: ⇒ String, uuid: String, shouldLog: Boolean, outputLogsPath: String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  25. def predict(chunks: Array[IndexedChunk], maxLen: Int, embeddingsDim: Int, configProtoBytes: Option[Array[Byte]] = None, includeConfidence: Boolean = false): Array[AssertionAnnotationWithLabel]

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

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  27. def tagsForTokens(labels: Array[Array[(String, Option[Double])]], pieces: Array[WordpieceEmbeddingsSentence]): Array[Array[(String, Option[Double])]]

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

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  29. val tensorflow: TensorflowWrapper

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  30. def toString(): String

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    Definition Classes
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  31. def train(trainDataset: Array[(WordpieceEmbeddingsSentence, AssertionAnnotationWithLabel)], lr: Float, batchSize: Int, dropout: Float, startEpoch: Int, endEpoch: Int, maxLen: Int, embeddingsDim: Int, graphFileName: String = "", test: Array[(WordpieceEmbeddingsSentence, AssertionAnnotationWithLabel)] = Array.empty, configProtoBytes: Option[Array[Byte]] = None, validationSplit: Float = 0.0f, enableOutputLogs: Boolean = false, outputLogsPath: String, uuid: String = Identifiable.randomUID("annotator")): Unit

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

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    Definition Classes
    TensorflowAssertion → Logging
  33. final def wait(): Unit

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    @throws( ... )
  34. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  35. final def wait(arg0: Long): Unit

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    @throws( ... )

Inherited from Logging

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