NAME
AI::MXNet::LRScheduler - The adaptive scheduler of the learning rate.
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DESCRIPTION
Learning rate scheduler, which adaptively changes the learning rate based on the
progress.
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new
base_lr : float (optional, default 0.01)
the initial learning rate
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call
Call to schedule current learning rate
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
a weight/index
Parameters
----------
$num_update: Int
the maximal number of updates applied to a weight.
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NAME
AI::MXNet::FactorScheduler - Reduces the learning rate by a factor.
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DESCRIPTION
Reduces the learning rate by a factor each step.
Assume the weight has been updated by n times, then the learning rate will
be base_lr * factor^(floor(n/step))
Parameters
----------
step: Int
schedule the learning rate update after n updates
factor: Num
the factor by which to reduce the learning rate.
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NAME
AI::MXNet::MultiFactorScheduler - Reduces the learning rate by an array ref of factors.
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DESCRIPTION
Reduces a learning rate in factor at steps specified in an array ref.
Assume the weight has been updated by n times, then the learning rate will
be base_lr * factor^(sum((step/n)<=1))
Parameters
----------
step: ArrayRef[Int]
schedule learning rate after n updates
factor: Num
the factor for reducing the learning rate
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