mxnet.lr_scheduler.FactorScheduler¶

class mxnet.lr_scheduler.FactorScheduler(step, factor=1, stop_factor_lr=1e-08, base_lr=0.01, warmup_steps=0, warmup_begin_lr=0, warmup_mode='linear')[source]¶

Reduce the learning rate by a factor for every n steps.

It returns a new learning rate by:

base_lr * pow(factor, floor(num_update/step))

Parameters

step (int) – Changes the learning rate for every n updates.
factor (float, optional) – The factor to change the learning rate.
stop_factor_lr (float, optional) – Stop updating the learning rate if it is less than this value.

__init__(step, factor=1, stop_factor_lr=1e-08, base_lr=0.01, warmup_steps=0, warmup_begin_lr=0, warmup_mode='linear')[source]¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`(step[, factor, stop_factor_lr, …])	Initialize self.
`get_warmup_lr`(num_update)