Package ai.djl.training.optimizer
Class Optimizer.OptimizerBuilder<T extends Optimizer.OptimizerBuilder>
- java.lang.Object
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- ai.djl.training.optimizer.Optimizer.OptimizerBuilder<T>
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- Direct Known Subclasses:
Adadelta.Builder
,Adagrad.Builder
,Adam.Builder
,Nag.Builder
,RmsProp.Builder
,Sgd.Builder
- Enclosing class:
- Optimizer
public abstract static class Optimizer.OptimizerBuilder<T extends Optimizer.OptimizerBuilder> extends java.lang.Object
The Builder to construct anOptimizer
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Constructor Summary
Constructors Modifier Constructor Description protected
OptimizerBuilder()
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Method Summary
All Methods Instance Methods Abstract Methods Concrete Methods Modifier and Type Method Description T
optBeginNumUpdate(int beginNumUpdate)
Sets the initial value of the number of updates.T
optClipGrad(float clipGrad)
Sets the value of the \(clipGrad\).T
optWeightDecays(float weightDecays)
Sets the value of weight decay.protected abstract T
self()
T
setRescaleGrad(float rescaleGrad)
Sets the value used to rescale the gradient.
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Method Detail
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setRescaleGrad
public T setRescaleGrad(float rescaleGrad)
Sets the value used to rescale the gradient. This is used to alleviate the effect of batching on the loss. Usually, the value is set to \( 1/batch_size \). Defaults to 1.- Parameters:
rescaleGrad
- the value used to rescale the gradient- Returns:
- this
Builder
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optWeightDecays
public T optWeightDecays(float weightDecays)
Sets the value of weight decay. Weight decay augments the objective function with a regularization term that penalizes large weights.- Parameters:
weightDecays
- the value of weight decay to be set- Returns:
- this
Builder
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optClipGrad
public T optClipGrad(float clipGrad)
Sets the value of the \(clipGrad\). Clips the gradient to the range of \([-clipGrad, clipGrad]\). If \(clipGrad \lt 0\), gradient clipping is turned off.\(grad = max(min(grad, clipGrad), -clipGrad)\)
- Parameters:
clipGrad
- the value of \(clipGrad\)- Returns:
- this
Builder
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optBeginNumUpdate
public T optBeginNumUpdate(int beginNumUpdate)
Sets the initial value of the number of updates.- Parameters:
beginNumUpdate
- the initial value of the number of updates- Returns:
- this
Builder
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self
protected abstract T self()
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