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
L1Regularizer, L2Regularizer
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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])

    l1

    l1 regularization rate

    l2

    l2 regularization rate

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. def accRegularization(parameter: Tensor[T], gradParameter: Tensor[T], scale: Double): Unit

    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
    L1L2Regularizer → Regularizer
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  7. def disable(): Unit

    Disable the regularization feature

    Disable the regularization feature

    Definition Classes
    Regularizer
  8. def enable(): Unit

    Enable the regularization feature

    Enable the regularization feature

    Definition Classes
    Regularizer
  9. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  10. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  11. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  12. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  13. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  14. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  15. val l1: Double
  16. val l2: Double
  17. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  19. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  20. def preCheck(parameter: Tensor[T], gradParameter: Tensor[T]): Boolean

    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
    Definition Classes
    AnyRef
  22. def toString(): String
    Definition Classes
    AnyRef → Any
  23. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  24. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  25. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Inherited from Regularizer[T]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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