Object/Trait

toolkit.neuralnetwork

DifferentiableField

Related Docs: trait DifferentiableField | package neuralnetwork

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object DifferentiableField

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Type Members

  1. case class GradientBinding(owner: DifferentiableField, gradientType: GradientType) extends Product with Serializable

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  2. case class GradientPort(df: DifferentiableField, jacobian: (libcog.Field) ⇒ libcog.Field, jacobianAdjoint: (libcog.Field) ⇒ libcog.Field) extends Product with Serializable

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  3. sealed trait GradientType extends AnyRef

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  4. case class Leaf(senders: Set[(DifferentiableField, Symbol)]) extends GradientType with Product with Serializable

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  5. case class Sender(senders: Set[(DifferentiableField, Symbol)]) extends GradientType with Product with Serializable

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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. def apply(field: libcog.Field, batchSize: Int): DifferentiableField

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  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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

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  11. def hashCode(): Int

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  12. final def isInstanceOf[T0]: Boolean

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

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  14. final def notify(): Unit

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  15. final def notifyAll(): Unit

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

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  17. def toString(): String

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  18. final def wait(): Unit

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

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

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