com.intel.analytics.bigdl.nn.abstractnn

AbstractCriterion

abstract class AbstractCriterion[A <: Activity, B <: Activity, T] extends Serializable

AbstractCriterion is an abstract class the concrete criterion should extend. Criterions are helpful to train a neural network. Given an input and a target, they compute the gradient according to a loss function.

It provides some important method such as forward, backward, updateOutput, updateGradInput frequently used as a criteria. Some of them need to be override in a concrete criterion class.

A

represents the input type of the criterion, which an be abstract type Activity, or concrete type Tensor or Table

B

represents the output type of the criterion

T

The numeric type in the criterion, usually which are Float or Double

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Instance Constructors

  1. new AbstractCriterion()(implicit arg0: ClassTag[A], arg1: ClassTag[B], arg2: ClassTag[T], ev: TensorNumeric[T])

Abstract Value Members

  1. abstract def updateGradInput(input: A, target: B): A

    Computing the gradient of the criterion with respect to its own input.

    Computing the gradient of the criterion with respect to its own input. This is returned in gradInput. Also, the gradInput state variable is updated accordingly.

    input

    input data

    target

    target data / labels

    returns

    gradient of input

Concrete Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
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  2. final def !=(arg0: Any): Boolean

    Definition Classes
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  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

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

    Definition Classes
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  6. final def asInstanceOf[T0]: T0

    Definition Classes
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  7. def backward(input: A, target: B): A

    Performs a back-propagation step through the criterion, with respect to the given input.

    Performs a back-propagation step through the criterion, with respect to the given input.

    input

    input data

    target

    target

    returns

    gradient corresponding to input data

  8. def canEqual(other: Any): Boolean

  9. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. def cloneCriterion(): AbstractCriterion[A, B, T]

    Deep copy this criterion

    Deep copy this criterion

    returns

    a deep copied criterion

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

    Definition Classes
    AnyRef
  12. def equals(other: Any): Boolean

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

    Attributes
    protected[java.lang]
    Definition Classes
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    Annotations
    @throws( classOf[java.lang.Throwable] )
  14. def forward(input: A, target: B): T

    Takes an input object, and computes the corresponding loss of the criterion, compared with target.

    Takes an input object, and computes the corresponding loss of the criterion, compared with target.

    input

    input data

    target

    target

    returns

    the loss of criterion

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

    Definition Classes
    AnyRef → Any
  16. var gradInput: A

  17. def hashCode(): Int

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

    Definition Classes
    Any
  19. final def ne(arg0: AnyRef): Boolean

    Definition Classes
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  20. final def notify(): Unit

    Definition Classes
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  21. final def notifyAll(): Unit

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  22. var output: T

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

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  24. def toString(): String

    Definition Classes
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  25. def updateOutput(input: A, target: B): T

    Computes the loss using input and objective function.

    Computes the loss using input and objective function. This function returns the result which is stored in the output field.

    input

    input of the criterion

    target

    target or labels

    returns

    the loss of the criterion

  26. final def wait(): Unit

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

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

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    @throws( ... )

Inherited from Serializable

Inherited from Serializable

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