Type

com.thoughtworks.deeplearning.plugins.FloatLayers

Implicits

Related Doc: package FloatLayers

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abstract type Implicits <: ImplicitsApi

Definition Classes
FloatLayersLayers
Source
FloatLayers.scala
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FloatLayers.ImplicitsApi, AnyRef, Any
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Type Members

  1. implicit final class FloatLayerOps[Operand0] extends AnyRef

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    An implicit wrapper that adds extension methods for differentiable float types that support the DeepLearning type class.

    An implicit wrapper that adds extension methods for differentiable float types that support the DeepLearning type class.

    Definition Classes
    ImplicitsApi

Value Members

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

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  2. final def ##(): Int

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

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  4. implicit def Float*Float[Operand0, Operand1, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], deepLearning1: DeepLearning.Aux[Operand1, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.*.Case[Operand0, Operand1] { type Result = Out }

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    Definition Classes
    ImplicitsApi
  5. implicit def Float+Float[Operand0, Operand1, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], deepLearning1: DeepLearning.Aux[Operand1, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.+.Case[Operand0, Operand1] { type Result = Out }

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    Definition Classes
    ImplicitsApi
  6. implicit def Float-Float[Operand0, Operand1, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], deepLearning1: DeepLearning.Aux[Operand1, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.-.Case[Operand0, Operand1] { type Result = Out }

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    Definition Classes
    ImplicitsApi
  7. implicit def Float/Float[Operand0, Operand1, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], deepLearning1: DeepLearning.Aux[Operand1, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators./.Case[Operand0, Operand1] { type Result = Out }

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    Definition Classes
    ImplicitsApi
  8. implicit def abs(Float)[Operand0, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.abs.Case[Operand0] { type Result = Out }

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    Definition Classes
    ImplicitsApi
  9. final def asInstanceOf[T0]: T0

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  10. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    AnyRef
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    @throws( ... )
  11. implicit def eagerFloatDsl[Differentiable, Data, Delta, Constructor, Out <: FloatLayer](implicit implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Dsl[Eager[Differentiable, Data, Delta], FloatLayer, Data]

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    Definition Classes
    ImplicitsApi
  12. final def eq(arg0: AnyRef): Boolean

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    AnyRef
  13. def equals(arg0: Any): Boolean

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  14. implicit def exp(Float)[Operand0, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.exp.Case[Operand0] { type Result = Out }

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    Definition Classes
    ImplicitsApi
  15. def finalize(): Unit

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    protected[java.lang]
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    Annotations
    @throws( classOf[java.lang.Throwable] )
  16. final def getClass(): Class[_]

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  17. def hashCode(): Int

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  18. implicit def implicitEager[Operand0](a: Operand0)(implicit deepLearning: DeepLearning[Operand0]): Eager[Operand0, Data, Delta]

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    ImplicitsApi
    Annotations
    @inline()
  19. final def isInstanceOf[T0]: Boolean

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  20. implicit def layerDeepLearning[From, Data0, Delta0](implicit asLayer: <:<[From, LayerApi { ... /* 2 definitions in type refinement */ }]): DeepLearning.Aux[From, Data0, Delta0]

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    Definition Classes
    ImplicitsApi
  21. implicit def log(Float)[Operand0, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.log.Case[Operand0] { type Result = Out }

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    ImplicitsApi
  22. implicit def max(Float,Float)[Operand0, Operand1, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], deepLearning1: DeepLearning.Aux[Operand1, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.max.Case[Operand0, Operand1] { type Result = Out }

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    ImplicitsApi
  23. implicit def min(Float,Float)[Operand0, Operand1, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], deepLearning1: DeepLearning.Aux[Operand1, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.min.Case[Operand0, Operand1] { type Result = Out }

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    ImplicitsApi
  24. final def ne(arg0: AnyRef): Boolean

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  25. final def notify(): Unit

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  26. final def notifyAll(): Unit

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  27. implicit def pow(Float,Float)[Operand0, Operand1, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], deepLearning1: DeepLearning.Aux[Operand1, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.pow.Case[Operand0, Operand1] { type Result = Out }

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    Definition Classes
    ImplicitsApi
  28. implicit def sqrt(Float)[Operand0, Out <: FloatLayer](implicit deepLearning0: DeepLearning.Aux[Operand0, Float, Float], implicitApply: feature.ImplicitApply.Aux[Rest, Out]): Operators.sqrt.Case[Operand0] { type Result = Out }

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    Definition Classes
    ImplicitsApi
  29. final def synchronized[T0](arg0: ⇒ T0): T0

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  30. def toString(): String

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  31. final def wait(): Unit

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    @throws( ... )
  32. final def wait(arg0: Long, arg1: Int): Unit

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

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Inherited from FloatLayers.ImplicitsApi

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