org.deeplearning4j.scalnet.layers.convolutional

Convolution

abstract class Convolution extends Node

Base class for convolutional layers.

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Instance Constructors

  1. new Convolution(dimension: Int, kernelSize: List[Int], stride: List[Int], padding: List[Int], dilation: List[Int], nChannels: Int = 0, nIn: Option[List[Int]] = scala.None, nFilter: Int = 0)

Abstract Value Members

  1. abstract def name: String

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Concrete 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. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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  8. def describe(): String

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  9. val dilation: List[Int]

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    protected
  10. val dimension: Int

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

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  12. def equals(arg0: Any): Boolean

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  13. def finalize(): Unit

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

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  15. def hashCode(): Int

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  16. def inputShape: List[Int]

    Definition Classes
    ConvolutionNode
  17. final def isInstanceOf[T0]: Boolean

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    Any
  18. val kernelSize: List[Int]

    Attributes
    protected
  19. val nChannels: Int

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    protected
  20. val nFilter: Int

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    protected
  21. val nIn: Option[List[Int]]

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

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  23. final def notify(): Unit

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  24. final def notifyAll(): Unit

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  25. def outputShape: List[Int]

    Definition Classes
    ConvolutionNode
  26. val padding: List[Int]

    Attributes
    protected
  27. def reshapeInput(nIn: List[Int]): Node

    Definition Classes
    Node
  28. val stride: List[Int]

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

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

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