Class/Object

com.intel.analytics.bigdl.optim

L1L2Regularizer

Related Docs: object L1L2Regularizer | package optim

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class L1L2Regularizer[T] extends Regularizer[T]

Apply both L1 and L2 regularization

T

type parameters Float or Double

Annotations
@SerialVersionUID()
Linear Supertypes
Regularizer[T], Serializable, Serializable, AnyRef, Any
Known Subclasses
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Inherited
  1. L1L2Regularizer
  2. Regularizer
  3. Serializable
  4. Serializable
  5. AnyRef
  6. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new L1L2Regularizer(l1: Double, l2: Double)(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

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    l1

    l1 regularization rate

    l2

    l2 regularization rate

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 accRegularization(parameter: Tensor[T], gradParameter: Tensor[T], scale: Double): Unit

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    The method need to be override by the concrete regularizer class It accumulates the gradient of the regularization of parameter to gradParameter

    The method need to be override by the concrete regularizer class It accumulates the gradient of the regularization of parameter to gradParameter

    parameter

    the parameter that is regularized

    gradParameter

    the gradient of the parameter

    scale

    the scale of gradParameters

    Definition Classes
    L1L2RegularizerRegularizer
  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 disable(): Unit

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    Disable the regularization feature

    Disable the regularization feature

    Definition Classes
    Regularizer
  8. def enable(): Unit

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    Enable the regularization feature

    Enable the regularization feature

    Definition Classes
    Regularizer
  9. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  10. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  11. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  12. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  13. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  14. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  15. val l1: Double

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    l1 regularization rate

  16. val l2: Double

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    l2 regularization rate

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

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    Definition Classes
    AnyRef
  18. final def notify(): Unit

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    Definition Classes
    AnyRef
  19. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  20. def preCheck(parameter: Tensor[T], gradParameter: Tensor[T]): Boolean

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    Check the regularization is applied or not

    Check the regularization is applied or not

    parameter

    the parameter that is regularized

    gradParameter

    the gradient of the parameter

    returns

    a boolean, if true, accumulates the gradient of regularization, otherwise not.

    Attributes
    protected
    Definition Classes
    Regularizer
  21. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  22. def toString(): String

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    Definition Classes
    AnyRef → Any
  23. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  24. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  25. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Regularizer[T]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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