FunctionalLayerModel

Value Members

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

   Definition Classes

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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

   Attributes

   protected[java.lang]

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8. def computePrevDelta(nextDelta: DenseMatrix[Double], input: DenseMatrix[Double], delta: DenseMatrix[Double]): Unit

   Computes the delta for back propagation.

   Computes the delta for back propagation. Delta is allocated based on the size provided by the LayerModel implementation and the stack (batch) size. Developer is responsible for checking the size of prevDelta when writing to it.

   delta

   delta of this layer

   Definition Classes

   FunctionalLayerModel → LayerModel

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

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10. def equals(arg0: Any): Boolean

    Definition Classes

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11. def eval(data: DenseMatrix[Double], output: DenseMatrix[Double]): Unit

    Evaluates the data (process the data through the layer).

    Evaluates the data (process the data through the layer). Output is allocated based on the size provided by the LayerModel implementation and the stack (batch) size. Developer is responsible for checking the size of output when writing to it.

    data

    data

    output

    output (modified in place)

    Definition Classes

    FunctionalLayerModel → LayerModel

12. def finalize(): Unit

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    protected[java.lang]

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

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14. def grad(delta: DenseMatrix[Double], input: DenseMatrix[Double], cumGrad: DenseVector[Double]): Unit

    Computes the gradient.

    Computes the gradient. cumGrad is a wrapper on the part of the weight vector. Size of cumGrad is based on weightSize provided by implementation of LayerModel.

    delta

    delta for this layer

    input

    input data

    cumGrad

    cumulative gradient (modified in place)

    Definition Classes

    FunctionalLayerModel → LayerModel

15. def hashCode(): Int

    Definition Classes

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16. final def isInstanceOf[T0]: Boolean

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17. val layer: FunctionalLayer

    functional layer

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

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19. final def notify(): Unit

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20. final def notifyAll(): Unit

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

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22. def toString(): String

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23. final def wait(): Unit

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

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

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26. val weights: DenseVector[Double]

    Definition Classes

    FunctionalLayerModel → LayerModel