Class

com.lewuathe.dllib.layer

SigmoidLayer

Related Doc: package layer

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class SigmoidLayer extends Layer with Visualizable

Sigmoid function layer

Linear Supertypes
Visualizable, Layer, Serializable, Serializable, AnyRef, Any
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Inherited
  1. SigmoidLayer
  2. Visualizable
  3. Layer
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
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Instance Constructors

  1. new SigmoidLayer(outputSize: Int, inputSize: Int)

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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(delta: Vector[Double], acts: ActivationStack, model: Model): (Vector[Double], Weight, Bias)

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    Calculate the delta of this iteration.

    Calculate the delta of this iteration. The input of the layer in forward phase can be restored from ActivationStack. It returns the delta of input layer of this layer and the delta of coefficient and intercept parameter.

    returns

    The delta tuple of the layer while back propagation. First is passed previous layer, the second and third is the delta of Weight and Bias parameter of the layer.

    Definition Classes
    SigmoidLayerLayer
  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  7. final def eq(arg0: AnyRef): Boolean

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

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

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  10. def forward(acts: ActivationStack, model: Model): Vector[Double]

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    Calculate the output corresponding given input.

    Calculate the output corresponding given input. Input is given as a top of ActivationStack.

    returns

    The output tuple of the layer. First value of the tuple represents the raw output, the second is applied activation function of the layer.

    Definition Classes
    SigmoidLayerLayer
  11. final def getClass(): Class[_]

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

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    Definition Classes
    AnyRef → Any
  13. var id: String

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    Definition Classes
    SigmoidLayerLayer
  14. val inputSize: Int

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    Definition Classes
    SigmoidLayerLayer
  15. final def isInstanceOf[T0]: Boolean

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

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

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

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    Definition Classes
    AnyRef
  19. val outputSize: Int

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

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    Definition Classes
    AnyRef
  21. def toString(): String

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    Definition Classes
    Layer → AnyRef → Any
  22. def vizWeight(outputPath: String, model: Model): Unit

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Visualizable

Inherited from Layer

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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