Modifier and Type | Interface and Description |
---|---|
interface |
LossFunction
A loss function for computing
the delta between two arrays
|
Modifier and Type | Class and Description |
---|---|
class |
BaseAccumulation
Base class for accumulation, initiates the initial entry
with respect to the child class.
|
class |
BaseLossFunction |
Modifier and Type | Method and Description |
---|---|
Accumulation |
OpExecutioner.execAndReturn(Accumulation op)
Execute and return the result from an accumulation
|
Accumulation |
DefaultOpExecutioner.execAndReturn(Accumulation op) |
Modifier and Type | Method and Description |
---|---|
INDArray |
OpExecutioner.exec(Accumulation accumulation,
int... dimension)
Execute an accumulation along a dimension
|
INDArray |
DefaultOpExecutioner.exec(Accumulation op,
int... dimension) |
Accumulation |
OpExecutioner.execAndReturn(Accumulation op)
Execute and return the result from an accumulation
|
Accumulation |
DefaultOpExecutioner.execAndReturn(Accumulation op) |
Modifier and Type | Method and Description |
---|---|
Accumulation |
OpFactory.createAccum(String name,
INDArray x)
Accumulation operation
|
Accumulation |
DefaultOpFactory.createAccum(String name,
INDArray x) |
Accumulation |
OpFactory.createAccum(String name,
INDArray x,
INDArray y) |
Accumulation |
DefaultOpFactory.createAccum(String name,
INDArray x,
INDArray y) |
Accumulation |
OpFactory.createAccum(String name,
INDArray x,
INDArray y,
INDArray z)
Accumulation operation
|
Accumulation |
DefaultOpFactory.createAccum(String name,
INDArray x,
INDArray y,
INDArray z) |
Modifier and Type | Class and Description |
---|---|
class |
Bias
Calculate a bias
|
class |
Dot
Dot product
|
class |
IAMax
Calculate the max over a vector
|
class |
Max
Calculate the max over a vector
|
class |
Mean
Calculate the mean of the vector
|
class |
Min
Calculate the min over a vector
|
class |
Norm1
Sum of absolute values
|
class |
Norm2
Sum of absolute values
|
class |
NormMax
The max absolute value
|
class |
Prod
Prod the components
|
class |
StandardDeviation
Standard deviation (sqrt of variance)
|
class |
Sum
Sum the components
|
class |
Variance
Variance with bias correction.
|
Modifier and Type | Class and Description |
---|---|
class |
CosineSimilarity
Cosine similarity
Note that you need to initialize
a scaling constant equal to the norm2 of the
vector
|
class |
EuclideanDistance
Euclidean distance
|
class |
ManhattanDistance
Manhattan distance
|
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