Table Of Contents
Table Of Contents

mx.nd.mp.sgd.mom.update

Description

Updater function for multi-precision sgd optimizer

Arguments

Argument

Description

weight

NDArray-or-Symbol.

Weight

grad

NDArray-or-Symbol.

Gradient

mom

NDArray-or-Symbol.

Momentum

weight32

NDArray-or-Symbol.

Weight32

lr

float, required.

Learning rate

momentum

float, optional, default=0.

The decay rate of momentum estimates at each epoch.

wd

float, optional, default=0.

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.

rescale.grad

float, optional, default=1.

Rescale gradient to grad = rescale_grad*grad.

clip.gradient

float, optional, default=-1.

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).

lazy.update

boolean, optional, default=1.

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

Value

out The result mx.ndarray