Interface ThresholdAlgorithm
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- All Superinterfaces:
Serializable
- All Known Implementing Classes:
AdaptiveThresholdAlgorithm
,FixedThresholdAlgorithm
,TargetSparsityThresholdAlgorithm
public interface ThresholdAlgorithm extends Serializable
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Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description double
calculateThreshold(int iteration, int epoch, Double lastThreshold, Boolean lastWasDense, Double lastSparsityRatio, INDArray updatesPlusResidual)
ThresholdAlgorithm
clone()
ThresholdAlgorithmReducer
newReducer()
Create a new ThresholdAlgorithmReducer.
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Method Detail
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calculateThreshold
double calculateThreshold(int iteration, int epoch, Double lastThreshold, Boolean lastWasDense, Double lastSparsityRatio, INDArray updatesPlusResidual)
- Parameters:
iteration
- Current neural network training iterationepoch
- Current neural network training epochlastThreshold
- The encoding threshold used in the last iteration - if available. May be null for first iteration in an epoch (where no 'last iteration' value is available)lastWasDense
- Whether the last encoding was dense (true) or sparse (false). May be null for the first iteration in an epoch (where no 'last iteration' value is available)lastSparsityRatio
- The sparsity ratio of the last iteration. Sparsity ratio is defined as numElements(encoded)/length(updates). A sparsity ratio of 1.0 would mean all entries present in encoded representation; a sparsity ratio of 0.0 would mean the encoded vector did not contain any values. Note: when the last encoding was dense, lastSparsityRatio is always null - this means that the sparsity ratio is larger than 1/16 = 0.0625updatesPlusResidual
- The actual array (updates plus residual) that will be encoded using the threshold calculated/returned by this method- Returns:
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newReducer
ThresholdAlgorithmReducer newReducer()
Create a new ThresholdAlgorithmReducer. Note that implementations should NOT add the curret ThresholdAlgorithm to it.- Returns:
- ThresholdAlgorithmReducer
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clone
ThresholdAlgorithm clone()
- Returns:
- A clone of the current threshold algorithm
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