case class NaturalExp(decay_step: Int, gamma: Double) extends LearningRateSchedule with Product with Serializable
NaturalExp is a learning rate schedule, which rescale the learning rate by exp ( -decay_rate * iter / decay_step ) referring to tensorflow's learning rate decay # natural_exp_decay
- decay_step
how often to apply decay
- gamma
the decay rate. e.g. 0.96
Linear Supertypes
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Instance Constructors
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new
NaturalExp(decay_step: Int, gamma: Double)
- decay_step
how often to apply decay
- gamma
the decay rate. e.g. 0.96
Value Members
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final
def
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val
currentRate: Double
- Definition Classes
- LearningRateSchedule
- val decay_step: Int
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- val gamma: Double
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def
updateHyperParameter[T](optimMethod: SGD[T]): Unit
update learning rate by config table and state table
update learning rate by config table and state table
- optimMethod
init optiMethod.
- Definition Classes
- NaturalExp → LearningRateSchedule
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final
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Deprecated Value Members
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def
updateHyperParameter(config: Table, state: Table): Unit
- Definition Classes
- LearningRateSchedule
- Annotations
- @deprecated
- Deprecated
(Since version 0.2.0) Please input SGD instead of Table