public class LossKLD extends Object implements ILossFunction
Constructor and Description |
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LossKLD() |
Modifier and Type | Method and Description |
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INDArray |
computeGradient(INDArray labels,
INDArray preOutput,
String activationFn,
INDArray mask)
Compute the gradient of the loss function with respect to the inputs: dL/dOutput
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org.apache.commons.math3.util.Pair<Double,INDArray> |
computeGradientAndScore(INDArray labels,
INDArray preOutput,
String activationFn,
INDArray mask,
boolean average)
Compute both the score (loss function value) and gradient.
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double |
computeScore(INDArray labels,
INDArray preOutput,
String activationFn,
INDArray mask,
boolean average)
Compute the score (loss function value) for the given inputs.
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INDArray |
computeScoreArray(INDArray labels,
INDArray preOutput,
String activationFn,
INDArray mask)
Compute the score (loss function value) for each example individually.
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String |
toString() |
public double computeScore(INDArray labels, INDArray preOutput, String activationFn, INDArray mask, boolean average)
ILossFunction
computeScore
in interface ILossFunction
labels
- Label/expected preOutputpreOutput
- Output of the model (neural network)activationFn
- Activation function that should be applied to preOutputmask
- Mask array; may be nullaverage
- Whether the score should be averaged (divided by number of rows in labels/preOutput) or not @return Loss function valuepublic INDArray computeScoreArray(INDArray labels, INDArray preOutput, String activationFn, INDArray mask)
ILossFunction
computeScoreArray
in interface ILossFunction
labels
- Labels/expected outputpreOutput
- Output of the model (neural network)activationFn
- Activation function that should be applied to preOutputmask
- @return Loss function value for each example; column vectorpublic INDArray computeGradient(INDArray labels, INDArray preOutput, String activationFn, INDArray mask)
ILossFunction
computeGradient
in interface ILossFunction
labels
- Label/expected outputpreOutput
- Output of the model (neural network), before the activation function is appliedactivationFn
- Activation function that should be applied to preOutputmask
- Mask array; may be nullpublic org.apache.commons.math3.util.Pair<Double,INDArray> computeGradientAndScore(INDArray labels, INDArray preOutput, String activationFn, INDArray mask, boolean average)
ILossFunction
ILossFunction.computeScore(INDArray, INDArray, String, INDArray, boolean)
and ILossFunction.computeGradient(INDArray, INDArray, String, INDArray)
individuallycomputeGradientAndScore
in interface ILossFunction
labels
- Label/expected outputpreOutput
- Output of the model (neural network)activationFn
- Activation function that should be applied to preOutputmask
- Mask array; may be nullaverage
- Whether the score should be averaged (divided by number of rows in labels/output) or notCopyright © 2016. All Rights Reserved.