Class/Object

org.deeplearning4j.scalnet.layers.convolutional

Convolution2D

Related Docs: object Convolution2D | package convolutional

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class Convolution2D extends Convolution with Layer

2D convolution for structured image-like inputs. Input should have three dimensions: height (number of rows), width (number of columns), and number of channels. Convolution is over height and width.

Linear Supertypes
Layer, Convolution, Node, AnyRef, Any
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Inherited
  1. Convolution2D
  2. Layer
  3. Convolution
  4. Node
  5. AnyRef
  6. Any
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Visibility
  1. Public
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Instance Constructors

  1. new Convolution2D(nFilter: Int, kernelSize: List[Int], nChannels: Int = 0, stride: List[Int] = List(1, 1), padding: List[Int] = List(0, 0), nIn: Option[List[Int]] = None, weightInit: WeightInit = WeightInit.XAVIER_UNIFORM, activation: Activation = Activation.IDENTITY, regularizer: WeightRegularizer = NoRegularizer(), dropOut: Double = 0.0, name: String = "")

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Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    AnyRef → Any

  4. val activation: Activation

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  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  7. def compile: Layer

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    Definition Classes
    Convolution2D → Layer

  8. def describe(): String

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    Definition Classes
    Node

  9. val dropOut: Double

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

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    Definition Classes
    AnyRef

  11. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  12. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

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    Definition Classes
    AnyRef → Any

  14. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  15. def inputShape: List[Int]

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    Definition Classes
    Convolution → Node

  16. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  17. val kernelSize: List[Int]

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    Attributes
    protected
    Definition Classes
    Convolution

  18. val nChannels: Int

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    Attributes
    protected
    Definition Classes
    Convolution

  19. val nFilter: Int

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    Attributes
    protected
    Definition Classes
    Convolution

  20. val nIn: Option[List[Int]]

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    Attributes
    protected
    Definition Classes
    Convolution

  21. val name: String

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    Definition Classes
    Convolution2D → Node

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

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    Definition Classes
    AnyRef

  23. final def notify(): Unit

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    Definition Classes
    AnyRef

  24. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  25. def outputShape: List[Int]

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    Definition Classes
    Convolution → Node

  26. val padding: List[Int]

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    Attributes
    protected
    Definition Classes
    Convolution

  27. val regularizer: WeightRegularizer

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  28. def reshapeInput(nIn: List[Int]): Convolution2D

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    Definition Classes
    Convolution2D → Node

  29. val stride: List[Int]

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    Attributes
    protected
    Definition Classes
    Convolution

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

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    Definition Classes
    AnyRef

  31. def toString(): String

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    Definition Classes
    AnyRef → Any

  32. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  35. val weightInit: WeightInit

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Inherited from Layer

Inherited from Convolution

Inherited from Node

Inherited from AnyRef

Inherited from Any

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