com.thoughtworks.deeplearning

DifferentiableAny

object DifferentiableAny

A namespace of common operators for any layers.

After importing DifferentiableAny._, the following methods will be available on any layers.

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Type Members

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

    A helper that contains common operations for any layers.

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

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

    A type class that makes result of forward as input of backward.

Value Members

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

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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

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  6. object Layers

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

  8. final def asInstanceOf[T0]: T0

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  9. def clone(): AnyRef

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

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  11. def equals(arg0: Any): Boolean

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  12. def finalize(): Unit

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

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  14. def hashCode(): Int

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  15. final def isInstanceOf[T0]: Boolean

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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

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

    Implicitly converts any layer to AnyLayerOps, which enables common methods for any layers.

    Implicitly converts any layer to AnyLayerOps, which enables common methods for any layers.

    Example:
    1. import com.thoughtworks.deeplearning.DifferentiableAny._
  21. def toString(): String

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  22. final def wait(): Unit

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

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

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