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com.thoughtworks.deeplearning

DifferentiableAny

Related Doc: package deeplearning

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object DifferentiableAny

Author:

杨博 (Yang Bo) <[email protected]>

Linear Supertypes
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Type Members

  1. final class AnyLayerOps[Input <: Batch, OutputData, OutputDelta] extends AnyRef

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    A helper that contains common ops for all layers

    A helper that contains common ops for all layers

    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
(input:From[INDArray]##`@`).compose(anotherLayer)

  2. type ExistentialNothing = T forSome {type T <: Nothing}

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  3. trait Trainable[-Data, +Delta] extends AnyRef

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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. object Layers

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  5. implicit def anyToLiteral: Aux[Any, Any, ExistentialNothing]

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    @throws( ... )

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

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )

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

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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

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  18. implicit def toAnyLayerOps[A, Input <: Batch, OutputData, OutputDelta](a: A)(implicit toLayer: Aux[A, Input, OutputData, OutputDelta]): AnyLayerOps[Input, OutputData, OutputDelta]

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    A helper that contains common boilerplate code for all layers.

    A helper that contains common boilerplate code for all layers.

    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._

  19. def toString(): String

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  20. final def wait(): Unit

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    @throws( ... )

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

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

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Inherited from AnyRef

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