com.intel.analytics.bigdl.optim

L1Regularizer

case class L1Regularizer[T](l1: Double)(implicit evidence$3: ClassTag[T], ev: TensorNumeric[T]) extends L1L2Regularizer[T] with Product with Serializable

Apply L1 regularization

T

type parameters Float or Double

l1

l1 regularization rate

Annotations
@SerialVersionUID( 1950693435414946281L )
Linear Supertypes
Product, Equals, L1L2Regularizer[T], Regularizer[T], Serializable, Serializable, AnyRef, Any
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Inherited
  1. L1Regularizer
  2. Product
  3. Equals
  4. L1L2Regularizer
  5. Regularizer
  6. Serializable
  7. Serializable
  8. AnyRef
  9. Any
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Instance Constructors

  1. new L1Regularizer(l1: Double)(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    l1

    l1 regularization rate

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
    AnyRef

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

    Definition Classes
    Any

  6. 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

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. def clone(): AnyRef

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

  9. def disable(): Unit

    Disable the regularization feature

    Disable the regularization feature

    Definition Classes
    Regularizer

  10. def enable(): Unit

    Enable the regularization feature

    Enable the regularization feature

    Definition Classes
    Regularizer

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

    Definition Classes
    AnyRef

  12. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  14. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  15. val l1: Double

    l1 regularization rate

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

    Definition Classes
    AnyRef

  17. final def notify(): Unit

    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  19. 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

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

    Definition Classes
    AnyRef

  21. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from L1L2Regularizer[T]

Inherited from Regularizer[T]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped