Trait

com.github.nearbydelta.deepspark.data

Activation

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trait Activation extends Differentiable

Trait that describes an activation function for each layer

Because these activation functions can be shared, we recommend to make inherited one as an object.

Linear Supertypes
Differentiable, (DataVec) ⇒ DataVec, Serializable, Serializable, AnyRef, Any
Known Subclasses
HardSigmoid, HardTanh, HyperbolicTangent, LeakyReLU, Linear, Rectifier, Sigmoid, Softmax, SoftmaxCEE, Softplus
Ordering
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Inherited
  1. Activation
  2. Differentiable
  3. Function1
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
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Abstract Value Members

  1. abstract def apply(v1: DataVec): DataVec

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    Definition Classes
    Function1

  2. abstract def derivative(fx: DataVec): Matrix

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    Differentiate function at output value fx.

    Differentiate function at output value fx.

    fx

    Differentiation point vector, by output value.

    returns

    Differentiation value of this function, generally squared matrix with same dimension.

    Definition Classes
    Differentiable

Concrete 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. def andThen[A](g: (DataVec) ⇒ A): (DataVec) ⇒ A

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    Definition Classes
    Function1
    Annotations
    @unspecialized()

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. def clone(): AnyRef

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

  7. def compose[A](g: (A) ⇒ DataVec): (A) ⇒ DataVec

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    Definition Classes
    Function1
    Annotations
    @unspecialized()

  8. def diffAtY(y: DataVec): Matrix

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    Differentiate function at output value y.

    Differentiate function at output value y.

    y

    Differentiation point vector, by output value.

    returns

    Differentiation value of this function, generally squared matrix with same dimension.

    Definition Classes
    Differentiable

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

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    Definition Classes
    AnyRef

  10. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  11. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  13. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  14. def initialize(fanIn: Int, fanOut: Int): (Double, Double)

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    Initialization range of weight

    Initialization range of weight

    fanIn

    the number of fan-in i.e. the number of neurons in previous layer

    fanOut

    the number of fan-out i.e. the number of neurons in next layer

    returns

    the initialized range of weight

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

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    Definition Classes
    AnyRef

  20. def toString(): String

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    Definition Classes
    Function1 → AnyRef → Any

  21. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Differentiable

Inherited from (DataVec) ⇒ DataVec

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped