Package org.nd4j.linalg.api.ops.impl.accum

Class Summary

Class	Description
All	Boolean AND accumulation
AMax	Calculate the absolute max over a vector
AMean	Calculate the absolute mean of the given vector
AMin	Calculate the absolute minimum over a vector
Any	Boolean AND pairwise transform
ASum	Absolute sum the components
Bias	Calculate a bias
CountNonZero	Count the number of non-zero elements
CountZero	Count the number of zero elements
CumProd
CumSum	Cumulative sum operation, optionally along dimension.
Dot	Dot product
Entropy	Entropy Op - returns the entropy (information gain, or uncertainty of a random variable).
EqualsWithEps	Operation for fast INDArrays equality checks
LogEntropy	Log Entropy Op - returns the entropy (information gain, or uncertainty of a random variable).
LogSumExp	LogSumExp - this op returns https://en.wikipedia.org/wiki/LogSumExp
MatchCondition	Absolute sum the components
Max	Calculate the max over a vector
Mean	Calculate the mean of the vector
Min	Calculate the min over a vector
Mmul	Matrix multiplication/dot product
Moments
Norm1	Sum of absolute values
Norm2	Sum of squared values (real) Sum of squared complex modulus (complex)
NormalizeMoments
NormMax	The max absolute value
Prod	Prod the components
ShannonEntropy	Non-normalized Shannon Entropy Op - returns the entropy (information gain, or uncertainty of a random variable).
SigmoidCrossEntropyLoss	Sigmoid cross entropy loss with logits
SoftmaxCrossEntropyLoss	Softmax cross entropy loss with logits
StandardDeviation	Standard deviation (sqrt of variance)
Sum	Sum the components
TensorMmul	TensorMmul
Variance	Variance with bias correction.
WeightedCrossEntropyLoss	Weighted cross entropy loss with logits
ZeroFraction	Compute the fraction of zero elements