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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 clone(): AnyRef

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6.  final def eq(arg0: AnyRef): Boolean

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7.  def equals(arg0: Any): Boolean

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8.  def finalize(): Unit

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9.  final def getClass(): Class[_]

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10.  def getLogName: String

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    Logging

11.  def getTFModel: TensorflowWrapper
12.  def graphInputDim: Int

    Length of the feature vector the graph expects.

    Length of the feature vector the graph expects. Feature vectors shorter than this are zero padded.

13.  def graphOutputDim: Int

    Number of output units of the graph.

    Number of output units of the graph. It can be greater than the number of classes of the training dataset, in which case the extra units are never used.

14.  def hashCode(): Int

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15.  def internalPredict(features: Array[Array[Float]], labels: Array[Array[Float]], configProtoBytes: Option[Array[Byte]] = None, classWeights: Array[Float]): (Float, Float)

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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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18.  def logMessage(message: String, uuid: String): Unit

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19.  val logger: Logger

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20.  val model: TensorflowWrapper
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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25.  val outputLogsPath: Option[String]
26.  def predict(features: Array[Array[Float]], configProtoBytes: Option[Array[Byte]] = None, allowedLabelIds: Option[Array[Int]] = None): (Array[Long], Array[Float], Array[Array[Float]])
27.  final def synchronized[T0](arg0: ⇒ T0): T0

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28.  def toString(): String

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29.  def train(features: Array[Array[Float]], labels: Array[Array[Float]], batchSize: Int, epochsNumber: Int, learningRate: Float = 0.001f, validationSplit: Float = 0.0f, classWeights: Array[Float], dropout: Float = 0.0f, configProtoBytes: Option[Array[Byte]] = None, uuid: String = Identifiable.randomUID("annotator"), resumeTraining: Boolean = false): Unit
30.  val verboseLevel: nlp.annotators.ner.Verbose.Value

    Definition Classes

    TensorflowGenericClassifier → Logging

31.  final def wait(): Unit

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

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

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