Class

com.intel.analytics.bigdl.optim.SGD

MultiStep

Related Doc: package SGD

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case class MultiStep(stepSizes: Array[Int], gamma: Double) extends LearningRateSchedule with Product with Serializable

similar to step but it allows non uniform steps defined by stepSizes

stepSizes

the series of step sizes used for lr decay

gamma

coefficient of decay

Linear Supertypes
Serializable, Serializable, Product, Equals, LearningRateSchedule, AnyRef, Any
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Inherited
  1. MultiStep
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. LearningRateSchedule
  7. AnyRef
  8. Any
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Instance Constructors

  1. new MultiStep(stepSizes: Array[Int], gamma: Double)

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    stepSizes

    the series of step sizes used for lr decay

    gamma

    coefficient of decay

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. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  5. def clone(): AnyRef

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

  6. var currentRate: Double

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    Definition Classes
    LearningRateSchedule

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

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    Definition Classes
    AnyRef

  8. def finalize(): Unit

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

  9. val gamma: Double

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    coefficient of decay

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

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    Definition Classes
    AnyRef → Any

  11. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    AnyRef

  13. final def notify(): Unit

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    Definition Classes
    AnyRef

  14. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  15. val stepSizes: Array[Int]

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    the series of step sizes used for lr decay

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

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    Definition Classes
    AnyRef

  17. def updateHyperParameter[T](optimMethod: SGD[T]): Unit

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    update learning rate by config table and state table

    update learning rate by config table and state table

    optimMethod

    init optiMethod.

    Definition Classes
    MultiStep → LearningRateSchedule

  18. def updateHyperParameter(config: Table, state: Table): Unit

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    Definition Classes
    MultiStep → LearningRateSchedule

  19. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from LearningRateSchedule

Inherited from AnyRef

Inherited from Any

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