org.apache.mxnet.javaapi

multi_mp_sgd_updateParam

Related Doc: package javaapi

class multi_mp_sgd_updateParam extends AnyRef

This Param Object is specifically used for multi_mp_sgd_update

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Instance Constructors

  1. new multi_mp_sgd_updateParam(data: Array[NDArray], lrs: Any, wds: Any)

    data

    Weights

    lrs

    Learning rates.

    wds

    Weight decay augments the objective function with a regularization term that penalizes large weights. The penalty scales with the square of the magnitude of each weight.

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

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

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  10. def getClip_gradient(): Float

  11. def getData(): Array[NDArray]

  12. def getLrs(): Any

  13. def getNum_weights(): Integer

  14. def getOut(): mxnet.NDArray

  15. def getRescale_grad(): Float

  16. def getWds(): Any

  17. def hashCode(): Int

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  20. final def notify(): Unit

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  21. final def notifyAll(): Unit

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  22. def setClip_gradient(clip_gradient: Float): multi_mp_sgd_updateParam

    clip_gradient

    Clip gradient to the range of [-clip_gradient, clip_gradient] If clip_gradient <= 0, gradient clipping is turned off. grad = max(min(grad, clip_gradient), -clip_gradient).

  23. def setNum_weights(num_weights: Integer): multi_mp_sgd_updateParam

    num_weights

    Number of updated weights.

  24. def setOut(out: NDArray): multi_mp_sgd_updateParam

  25. def setRescale_grad(rescale_grad: Float): multi_mp_sgd_updateParam

    rescale_grad

    Rescale gradient to grad = rescale_grad*grad.

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

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  27. def toString(): String

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  28. final def wait(): Unit

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