Class/Object

com.intel.analytics.zoo.pipeline.api.keras.objectives

MeanSquaredLogarithmicError

Related Docs: object MeanSquaredLogarithmicError | package objectives

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class MeanSquaredLogarithmicError[T] extends TensorLossFunction[T]

It calculates: first_log = K.log(K.clip(y, K.epsilon(), Double.MaxValue) + 1.) second_log = K.log(K.clip(x, K.epsilon(), Double.MaxValue) + 1.) and output K.mean(K.square(first_log - second_log))

Linear Supertypes
TensorLossFunction[T], LossFunction[Tensor[T], Tensor[T], T], AbstractCriterion[Tensor[T], Tensor[T], T], Serializable, Serializable, AnyRef, Any
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Inherited
  1. MeanSquaredLogarithmicError
  2. TensorLossFunction
  3. LossFunction
  4. AbstractCriterion
  5. Serializable
  6. Serializable
  7. AnyRef
  8. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new MeanSquaredLogarithmicError()(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

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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 backward(input: Tensor[T], target: Tensor[T]): Tensor[T]

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    Definition Classes
    AbstractCriterion

  6. def canEqual(other: Any): Boolean

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    Definition Classes
    AbstractCriterion

  7. def clone(): AnyRef

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

  8. def cloneCriterion(): AbstractCriterion[Tensor[T], Tensor[T], T]

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    Definition Classes
    AbstractCriterion

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

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    Definition Classes
    AnyRef

  10. def equals(other: Any): Boolean

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    Definition Classes
    AbstractCriterion → AnyRef → Any

  11. def finalize(): Unit

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

  12. def forward(input: Tensor[T], target: Tensor[T]): T

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    Definition Classes
    AbstractCriterion

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

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    Definition Classes
    AnyRef → Any

  14. var gradInput: Tensor[T]

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    Definition Classes
    AbstractCriterion

  15. def hashCode(): Int

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    Definition Classes
    AbstractCriterion → AnyRef → Any

  16. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  17. val loss: AbstractCriterion[Tensor[T], Tensor[T], T]

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    Definition Classes
    MeanSquaredLogarithmicError → LossFunction

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

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    Definition Classes
    AnyRef

  19. final def notify(): Unit

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    Definition Classes
    AnyRef

  20. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  21. var output: T

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    Definition Classes
    AbstractCriterion

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

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    Definition Classes
    AnyRef

  23. def toString(): String

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    Definition Classes
    AnyRef → Any

  24. def updateGradInput(input: Tensor[T], target: Tensor[T]): Tensor[T]

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    Definition Classes
    LossFunction → AbstractCriterion

  25. def updateOutput(input: Tensor[T], target: Tensor[T]): T

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    Definition Classes
    LossFunction → AbstractCriterion

  26. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from TensorLossFunction[T]

Inherited from LossFunction[Tensor[T], Tensor[T], T]

Inherited from AbstractCriterion[Tensor[T], Tensor[T], T]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped