org.apache.mxnet.javaapi

mp_sgd_mom_updateParam

Related Doc: package javaapi

class mp_sgd_mom_updateParam extends AnyRef

This Param Object is specifically used for mp_sgd_mom_update

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Instance Constructors

  1. new mp_sgd_mom_updateParam(weight: NDArray, grad: NDArray, mom: NDArray, weight32: NDArray, lr: Float)

    weight

    Weight

    grad

    Gradient

    mom

    Momentum

    weight32

    Weight32

    lr

    Learning rate

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  10. def getClip_gradient(): Float

  11. def getGrad(): NDArray

  12. def getLazy_update(): Boolean

  13. def getLr(): Float

  14. def getMom(): NDArray

  15. def getMomentum(): Float

  16. def getOut(): mxnet.NDArray

  17. def getRescale_grad(): Float

  18. def getWd(): Float

  19. def getWeight(): NDArray

  20. def getWeight32(): NDArray

  21. def hashCode(): Int

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  26. def setClip_gradient(clip_gradient: Float): mp_sgd_mom_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).

  27. def setLazy_update(lazy_update: Boolean): mp_sgd_mom_updateParam

    lazy_update

    If true, lazy updates are applied if gradient's stype is row_sparse and both weight and momentum have the same stype

  28. def setMomentum(momentum: Float): mp_sgd_mom_updateParam

    momentum

    The decay rate of momentum estimates at each epoch.

  29. def setOut(out: NDArray): mp_sgd_mom_updateParam

  30. def setRescale_grad(rescale_grad: Float): mp_sgd_mom_updateParam

    rescale_grad

    Rescale gradient to grad = rescale_grad*grad.

  31. def setWd(wd: Float): mp_sgd_mom_updateParam

    wd

    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.

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

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