public abstract class BaseUpdater extends Object implements Updater
Modifier and Type | Class and Description |
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protected static class |
BaseUpdater.UpdaterAggregatorImpl |
Modifier and Type | Field and Description |
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protected Map<String,org.nd4j.linalg.learning.GradientUpdater> |
updaterForVariable |
Constructor and Description |
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BaseUpdater() |
Modifier and Type | Method and Description |
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void |
applyLrDecayPolicy(LearningRatePolicy decay,
Layer layer,
int iteration,
String variable)
Update learning rate based on policy
|
void |
applyMomentumDecayPolicy(Layer layer,
int iteration,
String variable)
Update momentum if schedule exist
|
Updater |
clone() |
boolean |
equals(Object other) |
abstract void |
init() |
abstract org.nd4j.linalg.learning.GradientUpdater |
init(String variable,
org.nd4j.linalg.api.ndarray.INDArray gradient,
Layer layer) |
void |
postApply(Layer layer,
org.nd4j.linalg.api.ndarray.INDArray gradient,
String param,
int miniBatchSize)
Apply the regularization
|
void |
preApply(Layer layer,
Gradient gradient,
int iteration)
Apply gradient normalization: scale based on L2, clipping etc.
|
void |
update(Layer layer,
Gradient gradient,
int iteration,
int miniBatchSize)
Updater: updates the model
|
finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getAggregator
public void update(Layer layer, Gradient gradient, int iteration, int miniBatchSize)
Updater
public void postApply(Layer layer, org.nd4j.linalg.api.ndarray.INDArray gradient, String param, int miniBatchSize)
layer
- gradient
- param
- public void applyMomentumDecayPolicy(Layer layer, int iteration, String variable)
public void applyLrDecayPolicy(LearningRatePolicy decay, Layer layer, int iteration, String variable)
public void preApply(Layer layer, Gradient gradient, int iteration)
public abstract void init()
public abstract org.nd4j.linalg.learning.GradientUpdater init(String variable, org.nd4j.linalg.api.ndarray.INDArray gradient, Layer layer)
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