Class | Description |
---|---|
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
|
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
|
Copyright © 2018. All rights reserved.