Class

org.deeplearning4j.spark.impl.paramavg

BaseTrainingWorker

Related Doc: package paramavg

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abstract class BaseTrainingWorker[R <: TrainingResult] extends TrainingWorker[R]

Linear Supertypes
TrainingWorker[R], Serializable, AnyRef, Any
Known Subclasses
ParameterAveragingTrainingWorker
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  1. BaseTrainingWorker
  2. TrainingWorker
  3. Serializable
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Instance Constructors

  1. new BaseTrainingWorker()

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Abstract Value Members

  1. abstract def addHook(trainingHook: TrainingHook): Unit

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    Definition Classes
    TrainingWorker

  2. abstract def getDataConfiguration(): WorkerConfiguration

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    Definition Classes
    TrainingWorker

  3. abstract def getFinalResult(graph: ComputationGraph): R

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    Definition Classes
    TrainingWorker

  4. abstract def getFinalResult(network: MultiLayerNetwork): R

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    Definition Classes
    TrainingWorker

  5. abstract def getFinalResultNoData(): R

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    Definition Classes
    TrainingWorker

  6. abstract def getFinalResultNoDataWithStats(): Pair[R, SparkTrainingStats]

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    Definition Classes
    TrainingWorker

  7. abstract def getFinalResultWithStats(graph: ComputationGraph): Pair[R, SparkTrainingStats]

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    Definition Classes
    TrainingWorker

  8. abstract def getFinalResultWithStats(network: MultiLayerNetwork): Pair[R, SparkTrainingStats]

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    Definition Classes
    TrainingWorker

  9. abstract def getInitialModel(): MultiLayerNetwork

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    Definition Classes
    TrainingWorker

  10. abstract def getInitialModelGraph(): ComputationGraph

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    Definition Classes
    TrainingWorker

  11. abstract def processMinibatch(dataSet: MultiDataSet, graph: ComputationGraph, isLast: Boolean): R

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    Definition Classes
    TrainingWorker

  12. abstract def processMinibatch(dataSet: DataSet, graph: ComputationGraph, isLast: Boolean): R

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    Definition Classes
    TrainingWorker

  13. abstract def processMinibatch(dataSet: DataSet, network: MultiLayerNetwork, isLast: Boolean): R

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    Definition Classes
    TrainingWorker

  14. abstract def processMinibatchWithStats(dataSet: MultiDataSet, graph: ComputationGraph, isLast: Boolean): Pair[R, SparkTrainingStats]

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    Definition Classes
    TrainingWorker

  15. abstract def processMinibatchWithStats(dataSet: DataSet, graph: ComputationGraph, isLast: Boolean): Pair[R, SparkTrainingStats]

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    Definition Classes
    TrainingWorker

  16. abstract def processMinibatchWithStats(dataSet: DataSet, network: MultiLayerNetwork, isLast: Boolean): Pair[R, SparkTrainingStats]

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    Definition Classes
    TrainingWorker

  17. abstract def removeHook(trainingHook: TrainingHook): Unit

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    Definition Classes
    TrainingWorker

Concrete 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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  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 hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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

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  16. def toString(): String

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  17. final def wait(): Unit

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

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

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Inherited from TrainingWorker[R]

Inherited from Serializable

Inherited from AnyRef

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