com.intel.analytics.bigdl.models.inception.Options

TrainParams

case class TrainParams(folder: String = "./", checkpoint: Option[String] = scala.None, modelSnapshot: Option[String] = scala.None, stateSnapshot: Option[String] = scala.None, classNumber: Int = 1000, batchSize: Int = -1, learningRate: Double = 0.01, env: String = "local", overWriteCheckpoint: Boolean = false, maxEpoch: Option[Int] = scala.None, maxIteration: Int = 62000, weightDecay: Double = 1.0E-4, checkpointIteration: Int = 620, graphModel: Boolean = false, maxLr: Option[Double] = scala.None, warmupEpoch: Option[Int] = scala.None, gradientL2NormThreshold: Option[Double] = scala.None, gradientMin: Option[Double] = scala.None, gradientMax: Option[Double] = scala.None, optimizerVersion: Option[String] = scala.None) extends Product with Serializable

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Instance Constructors

  1. new TrainParams(folder: String = "./", checkpoint: Option[String] = scala.None, modelSnapshot: Option[String] = scala.None, stateSnapshot: Option[String] = scala.None, classNumber: Int = 1000, batchSize: Int = -1, learningRate: Double = 0.01, env: String = "local", overWriteCheckpoint: Boolean = false, maxEpoch: Option[Int] = scala.None, maxIteration: Int = 62000, weightDecay: Double = 1.0E-4, checkpointIteration: Int = 620, graphModel: Boolean = false, maxLr: Option[Double] = scala.None, warmupEpoch: Option[Int] = scala.None, gradientL2NormThreshold: Option[Double] = scala.None, gradientMin: Option[Double] = scala.None, gradientMax: Option[Double] = scala.None, optimizerVersion: Option[String] = scala.None)

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
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  5. final def ==(arg0: Any): Boolean

    Definition Classes
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  6. final def asInstanceOf[T0]: T0

    Definition Classes
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  7. val batchSize: Int

  8. val checkpoint: Option[String]

  9. val checkpointIteration: Int

  10. val classNumber: Int

  11. def clone(): AnyRef

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

  12. val env: String

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

    Definition Classes
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  14. def finalize(): Unit

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

  15. val folder: String

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

    Definition Classes
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  17. val gradientL2NormThreshold: Option[Double]

  18. val gradientMax: Option[Double]

  19. val gradientMin: Option[Double]

  20. val graphModel: Boolean

  21. final def isInstanceOf[T0]: Boolean

    Definition Classes
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  22. val learningRate: Double

  23. val maxEpoch: Option[Int]

  24. val maxIteration: Int

  25. val maxLr: Option[Double]

  26. val modelSnapshot: Option[String]

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

    Definition Classes
    AnyRef

  28. final def notify(): Unit

    Definition Classes
    AnyRef

  29. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  30. val optimizerVersion: Option[String]

  31. val overWriteCheckpoint: Boolean

  32. val stateSnapshot: Option[String]

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

    Definition Classes
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  34. final def wait(): Unit

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    @throws( ... )

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

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    @throws( ... )

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

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    @throws( ... )

  37. val warmupEpoch: Option[Int]

  38. val weightDecay: Double

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Inherited from Product

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