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

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7.  val encoder: NerDatasetEncoder
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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12.  def getLogName: String

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    TensorflowNer → Logging

13.  def getPiecesTags(tokenTags: Array[TextSentenceLabels], sentences: Array[WordpieceEmbeddingsSentence]): Array[Array[String]]
14.  def getPiecesTags(tokenTags: TextSentenceLabels, sentence: WordpieceEmbeddingsSentence): Array[String]
15.  def hashCode(): Int

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16.  final def isInstanceOf[T0]: Boolean

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

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    Logging

18.  val logger: Logger

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    protected

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    Logging

19.  def measure(labeled: Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]], extended: Boolean = false, enableOutputLogs: Boolean = false, outputLogsPath: String, batchSize: Int = 8, uuid: String = Identifiable.randomUID("annotator")): (Float, Float)
20.  final def ne(arg0: AnyRef): Boolean

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21.  final def notify(): Unit

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22.  final def notifyAll(): Unit

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

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    Logging

24.  def predict(dataset: Array[WordpieceEmbeddingsSentence], configProtoBytes: Option[Array[Byte]], includeConfidence: Boolean, includeAllConfidenceScores: Boolean, batchSize: Int): Array[Array[(String, Option[Array[Map[String, String]]])]]
25.  def saveBestModel(): Session
26.  final def synchronized[T0](arg0: ⇒ T0): T0

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27.  def tagsForTokens(labels: Array[Array[(String, Option[Array[Map[String, String]]])]], pieces: Array[WordpieceEmbeddingsSentence]): Array[Array[(String, Option[Array[Map[String, String]]])]]
28.  def tagsForTokens(labels: Array[(String, Option[Array[Map[String, String]]])], pieces: WordpieceEmbeddingsSentence): Array[(String, Option[Array[Map[String, String]]])]
29.  val tensorflow: TensorflowWrapper
30.  def toString(): String

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31.  def train(trainDataset: ⇒ Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]], trainLength: Long, validDataset: ⇒ Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]], validLength: Long, lr: Float, po: Float, dropout: Float, batchSize: Int = 8, useBestModel: Boolean = false, bestModelMetricPreference: String = ModelMetrics.microF1, startEpoch: Int = 0, endEpoch: Int, graphFileName: String = "", test: ⇒ Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]] = Iterator.empty, configProtoBytes: Option[Array[Byte]] = None, validationSplit: Float = 0.0f, evaluationLogExtended: Boolean = false, includeConfidence: Boolean = false, enableOutputLogs: Boolean = false, outputLogsPath: String, uuid: String = Identifiable.randomUID("annotator")): Session
32.  val verboseLevel: nlp.annotators.ner.Verbose.Value

    Definition Classes

    TensorflowNer → Logging

33.  final def wait(): Unit

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

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35.  final def wait(arg0: Long): Unit

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