Package org.deeplearning4j.earlystopping
Class EarlyStoppingConfiguration.Builder<T extends Model>
- java.lang.Object
-
- org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder<T>
-
- Enclosing class:
- EarlyStoppingConfiguration<T extends Model>
public static class EarlyStoppingConfiguration.Builder<T extends Model> extends Object
-
-
Constructor Summary
Constructors Constructor Description Builder()
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description EarlyStoppingConfiguration<T>
build()
Create the early stopping configurationEarlyStoppingConfiguration.Builder<T>
epochTerminationConditions(List<EpochTerminationCondition> terminationConditions)
Termination conditions to be evaluated every N epochs, with N set by evaluateEveryNEpochs optionEarlyStoppingConfiguration.Builder<T>
epochTerminationConditions(EpochTerminationCondition... terminationConditions)
Termination conditions to be evaluated every N epochs, with N set by evaluateEveryNEpochs optionEarlyStoppingConfiguration.Builder<T>
evaluateEveryNEpochs(int everyNEpochs)
How frequently should evaluations be conducted (in terms of epochs)? Defaults to every (1) epochs.EarlyStoppingConfiguration.Builder<T>
iterationTerminationConditions(IterationTerminationCondition... terminationConditions)
Termination conditions to be evaluated every iteration (minibatch)EarlyStoppingConfiguration.Builder<T>
modelSaver(EarlyStoppingModelSaver<T> modelSaver)
How should models be saved? (Default: in memory)EarlyStoppingConfiguration.Builder<T>
saveLastModel(boolean saveLastModel)
Save the last model? If true: save the most recent model at each epoch, in addition to the best model (whenever the best model improves).EarlyStoppingConfiguration.Builder<T>
scoreCalculator(ScoreCalculator scoreCalculator)
Score calculator.EarlyStoppingConfiguration.Builder<T>
scoreCalculator(Supplier<ScoreCalculator> scoreCalculatorSupplier)
Score calculator.
-
-
-
Method Detail
-
modelSaver
public EarlyStoppingConfiguration.Builder<T> modelSaver(EarlyStoppingModelSaver<T> modelSaver)
How should models be saved? (Default: in memory)
-
epochTerminationConditions
public EarlyStoppingConfiguration.Builder<T> epochTerminationConditions(EpochTerminationCondition... terminationConditions)
Termination conditions to be evaluated every N epochs, with N set by evaluateEveryNEpochs option
-
epochTerminationConditions
public EarlyStoppingConfiguration.Builder<T> epochTerminationConditions(List<EpochTerminationCondition> terminationConditions)
Termination conditions to be evaluated every N epochs, with N set by evaluateEveryNEpochs option
-
iterationTerminationConditions
public EarlyStoppingConfiguration.Builder<T> iterationTerminationConditions(IterationTerminationCondition... terminationConditions)
Termination conditions to be evaluated every iteration (minibatch)
-
saveLastModel
public EarlyStoppingConfiguration.Builder<T> saveLastModel(boolean saveLastModel)
Save the last model? If true: save the most recent model at each epoch, in addition to the best model (whenever the best model improves). If false: only save the best model. Default: false Useful for example if you might want to continue training after a max-time terminatino condition occurs.
-
evaluateEveryNEpochs
public EarlyStoppingConfiguration.Builder<T> evaluateEveryNEpochs(int everyNEpochs)
How frequently should evaluations be conducted (in terms of epochs)? Defaults to every (1) epochs.
-
scoreCalculator
public EarlyStoppingConfiguration.Builder<T> scoreCalculator(ScoreCalculator scoreCalculator)
Score calculator. Used to calculate a score (such as loss function on a test set), every N epochs, where N is set byevaluateEveryNEpochs
-
scoreCalculator
public EarlyStoppingConfiguration.Builder<T> scoreCalculator(Supplier<ScoreCalculator> scoreCalculatorSupplier)
Score calculator. Used to calculate a score (such as loss function on a test set), every N epochs, where N is set byevaluateEveryNEpochs
-
build
public EarlyStoppingConfiguration<T> build()
Create the early stopping configuration
-
-