Class

org.deeplearning4j.spark.impl.paramavg

ParameterAveragingTrainingMaster

Related Doc: package paramavg

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class ParameterAveragingTrainingMaster extends BaseTrainingMaster[ParameterAveragingTrainingResult, ParameterAveragingTrainingWorker] with TrainingMaster[ParameterAveragingTrainingResult, ParameterAveragingTrainingWorker]

Linear Supertypes
BaseTrainingMaster[ParameterAveragingTrainingResult, ParameterAveragingTrainingWorker], TrainingMaster[ParameterAveragingTrainingResult, ParameterAveragingTrainingWorker], AnyRef, Any
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Inherited
  1. ParameterAveragingTrainingMaster
  2. BaseTrainingMaster
  3. TrainingMaster
  4. AnyRef
  5. Any
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Visibility
  1. Public
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Instance Constructors

  1. new ParameterAveragingTrainingMaster(saveUpdater: Boolean, numWorkers: Integer, rddDataSetNumExamples: Int, batchSizePerWorker: Int, averagingFrequency: Int, aggregationDepth: Int, prefetchNumBatches: Int, repartition: Repartition, repartitionStrategy: RepartitionStrategy, storageLevel: StorageLevel, collectTrainingStats: Boolean)

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  2. new ParameterAveragingTrainingMaster(saveUpdater: Boolean, numWorkers: Integer, rddDataSetNumExamples: Int, batchSizePerWorker: Int, averagingFrequency: Int, aggregationDepth: Int, prefetchNumBatches: Int, repartition: Repartition, repartitionStrategy: RepartitionStrategy, collectTrainingStats: Boolean)

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  3. new ParameterAveragingTrainingMaster(saveUpdater: Boolean, numWorkers: Integer, rddDataSetNumExamples: Int, batchSizePerWorker: Int, averagingFrequency: Int, prefetchNumBatches: Int)

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  4. new ParameterAveragingTrainingMaster(builder: Builder)

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  5. new ParameterAveragingTrainingMaster()

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  4. def addHook(trainingHook: TrainingHook): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  7. def deleteTempDir(sc: JavaSparkContext, tempDirPath: String): Boolean

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]
    Definition Classes
    BaseTrainingMaster

  8. def deleteTempFiles(sc: SparkContext): Boolean

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    Definition Classes
    BaseTrainingMaster → TrainingMaster

  9. def deleteTempFiles(sc: JavaSparkContext): Boolean

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    Definition Classes
    BaseTrainingMaster → TrainingMaster

  10. def doIteration(graph: SparkComputationGraph, split: JavaRDD[MultiDataSet], splitNum: Int, numSplits: Int): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  11. def doIteration(network: SparkDl4jMultiLayer, split: JavaRDD[DataSet], splitNum: Int, numSplits: Int): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  12. def doIterationPDS(network: SparkDl4jMultiLayer, graph: SparkComputationGraph, split: JavaRDD[PortableDataStream], splitNum: Int, numSplits: Int): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  13. def doIterationPDS_MDS(graph: SparkComputationGraph, split: JavaRDD[PortableDataStream], splitNum: Int, numSplits: Int): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  14. def doIterationPaths(network: SparkDl4jMultiLayer, graph: SparkComputationGraph, split: JavaRDD[String], splitNum: Int, numSplits: Int, dataSetObjectNumExamples: Int): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  15. def doIterationPathsMDS(graph: SparkComputationGraph, split: JavaRDD[String], splitNum: Int, numSplits: Int, dataSetObjectNumExamples: Int): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

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

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    Definition Classes
    AnyRef

  17. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  18. def executeTraining(graph: SparkComputationGraph, trainingData: JavaPairRDD[String, PortableDataStream]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  19. def executeTraining(graph: SparkComputationGraph, trainingData: JavaRDD[DataSet]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  20. def executeTraining(network: SparkDl4jMultiLayer, trainingData: JavaPairRDD[String, PortableDataStream]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  21. def executeTraining(network: SparkDl4jMultiLayer, trainingData: JavaRDD[DataSet]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  22. def executeTrainingDirect(graph: SparkComputationGraph, trainingData: JavaRDD[MultiDataSet]): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  23. def executeTrainingDirect(network: SparkDl4jMultiLayer, trainingData: JavaRDD[DataSet]): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  24. def executeTrainingMDS(graph: SparkComputationGraph, trainingData: JavaPairRDD[String, PortableDataStream]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  25. def executeTrainingMDS(graph: SparkComputationGraph, trainingData: JavaRDD[MultiDataSet]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  26. def executeTrainingPaths(network: SparkComputationGraph, trainingDataPaths: JavaRDD[String]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  27. def executeTrainingPaths(network: SparkDl4jMultiLayer, trainingDataPaths: JavaRDD[String]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  28. def executeTrainingPathsHelper(network: SparkDl4jMultiLayer, trainingDataPaths: JavaRDD[String], dataSetObjectsNumExamples: Int): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  29. def executeTrainingPathsMDS(network: SparkComputationGraph, trainingMultiDataPaths: JavaRDD[String]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  30. def executeTrainingPathsMDSHelper(network: SparkComputationGraph, trainingMultiDataPaths: JavaRDD[String], dataSetObjectsNumExamples: Int): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  31. def export(trainingData: JavaRDD[DataSet]): String

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]
    Definition Classes
    BaseTrainingMaster

  32. def exportIfRequired(sc: JavaSparkContext, trainingData: JavaRDD[DataSet]): JavaRDD[String]

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]
    Definition Classes
    BaseTrainingMaster

  33. def exportIfRequiredMDS(sc: JavaSparkContext, trainingData: JavaRDD[MultiDataSet]): JavaRDD[String]

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]
    Definition Classes
    BaseTrainingMaster

  34. def exportMDS(trainingData: JavaRDD[MultiDataSet]): String

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]
    Definition Classes
    BaseTrainingMaster

  35. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  36. def getBaseDirForRDD(rdd: JavaRDD[_]): String

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]
    Definition Classes
    BaseTrainingMaster

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

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    Definition Classes
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  38. def getDefaultExportDirectory(sc: SparkContext): String

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]
    Definition Classes
    BaseTrainingMaster

  39. def getIsCollectTrainingStats(): Boolean

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  40. def getNumDataSetObjectsPerSplit(numExamplesEachRddObject: Int): Int

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  41. def getRouterProvider(): StatsStorageRouterProvider

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  42. def getSplitRDDs[T](trainingData: JavaRDD[T], totalDataSetObjectCount: Int, examplesPerDataSetObject: Int): Array[JavaRDD[T]]

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  43. def getSplitRDDs[T, Repr](trainingData: JavaPairRDD[T, Repr], totalDataSetObjectCount: Int): Array[JavaPairRDD[T, Repr]]

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  44. def getTotalDataSetObjectCount[T, Repr <: JavaRDDLike[T, Repr]](trainingData: JavaRDDLike[T, Repr]): Long

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  45. def getTrainingStats(): SparkTrainingStats

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  46. def getWorkerInstance(graph: SparkComputationGraph): ParameterAveragingTrainingWorker

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  47. def getWorkerInstance(network: SparkDl4jMultiLayer): ParameterAveragingTrainingWorker

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  48. def hashCode(): Int

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  49. final def isInstanceOf[T0]: Boolean

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

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  51. final def notify(): Unit

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  52. final def notifyAll(): Unit

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  53. def numObjectsEachWorker(numExamplesEachRddObject: Int): Int

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  54. def processResults(network: SparkDl4jMultiLayer, graph: SparkComputationGraph, results: JavaRDD[ParameterAveragingTrainingResult], splitNum: Int, totalSplits: Int): Unit

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    Attributes
    protected[org.deeplearning4j.spark.impl.paramavg]

  55. def removeHook(trainingHook: TrainingHook): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  56. def setCollectTrainingStats(collectTrainingStats: Boolean): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  57. def setListeners(statsStorage: StatsStorageRouter, listeners: Collection[IterationListener]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  58. def setListeners(listeners: Collection[IterationListener]): Unit

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

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

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    Definition Classes
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  60. def toJson(): String

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  61. def toString(): String

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    AnyRef → Any

  62. def toYaml(): String

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    Definition Classes
    ParameterAveragingTrainingMaster → TrainingMaster

  63. final def wait(): Unit

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    @throws( ... )

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

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    @throws( ... )

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

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Inherited from BaseTrainingMaster[ParameterAveragingTrainingResult, ParameterAveragingTrainingWorker]

Inherited from TrainingMaster[ParameterAveragingTrainingResult, ParameterAveragingTrainingWorker]

Inherited from AnyRef

Inherited from Any

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