Class for reducing learning rate in factor
Assume the weight has been updated by n times, then the learning rate will
be base_lr * factor^^(floor(n/step))
Int, schedule learning rate after n updates
Float, the factor for reducing the learning rate
Base class of a learning rate scheduler
The training progress is presented by num_update, which can be roughly
viewed as the number of minibatches executed so far. Its value is
non-decreasing, and increases at most by one.
The exact value is the upper bound of the number of updates applied to
Int, the maximal number of updates applied to a weight.