Table Of Contents
Table Of Contents

mx.nd.signsgd.update

Description

Update function for SignSGD optimizer.

\[\begin{split} g_t = \nabla J(W_{t-1})\\ W_t = W_{t-1} - \eta_t \text{sign}(g_t)\end{split}\]

It updates the weights using:

weight = weight - learning_rate * sign(gradient)

.. note::       - sparse ndarray not supported for this optimizer yet.

Arguments

Argument

Description

weight

NDArray-or-Symbol.

Weight

grad

NDArray-or-Symbol.

Gradient

lr

float, required.

Learning rate

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).