class KullbackLeiblerDivergenceCriterion[T] extends TensorCriterion[T]
This method is same as kullback_leibler_divergence loss in keras.
Loss calculated as:
y_true = K.clip(y_true, K.epsilon(), 1)
y_pred = K.clip(y_pred, K.epsilon(), 1)
and output K.sum(y_true * K.log(y_true / y_pred), axis=-1)
- T
The numeric type in the criterion, usually which are Float or Double
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- new KullbackLeiblerDivergenceCriterion()(implicit arg0: ClassTag[T], ev: TensorNumeric[T])
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def
backward(input: Tensor[T], target: Tensor[T]): Tensor[T]
Performs a back-propagation step through the criterion, with respect to the given input.
Performs a back-propagation step through the criterion, with respect to the given input.
- input
input data
- target
target
- returns
gradient corresponding to input data
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- var bufferInput: Tensor[T]
- var bufferTarget: Tensor[T]
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cloneCriterion(): AbstractCriterion[Tensor[T], Tensor[T], T]
Deep copy this criterion
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def
forward(input: Tensor[T], target: Tensor[T]): T
Takes an input object, and computes the corresponding loss of the criterion, compared with
target.Takes an input object, and computes the corresponding loss of the criterion, compared with
target.- input
input data
- target
target
- returns
the loss of criterion
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gradInput: Tensor[T]
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def
updateGradInput(input: Tensor[T], target: Tensor[T]): Tensor[T]
back propagation with: - target / input
back propagation with: - target / input
- input
input data
- target
target data / labels
- returns
gradient of input
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- KullbackLeiblerDivergenceCriterion → AbstractCriterion
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def
updateOutput(input: Tensor[T], target: Tensor[T]): T
It calculates: y_true = K.clip(y_true, K.epsilon(), 1) y_pred = K.clip(y_pred, K.epsilon(), 1) and output K.sum(y_true * K.log(y_true / y_pred), axis=-1)
It calculates: y_true = K.clip(y_true, K.epsilon(), 1) y_pred = K.clip(y_pred, K.epsilon(), 1) and output K.sum(y_true * K.log(y_true / y_pred), axis=-1)
- input
input of the criterion
- target
target or labels
- returns
the loss of the criterion
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- KullbackLeiblerDivergenceCriterion → AbstractCriterion
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