public class NormMax extends BaseAccumulation
finalResult, isComplex, keepDims, newFormat
extraArgs, extraArgz, n, numProcessed, passThrough, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
NormMax() |
NormMax(INDArray x) |
NormMax(INDArray x,
INDArray y) |
NormMax(INDArray x,
INDArray y,
INDArray z,
long n) |
NormMax(INDArray x,
INDArray y,
long n) |
NormMax(SameDiff sameDiff,
SDVariable i_v,
int[] dimensions) |
NormMax(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
int[] dimensions) |
Modifier and Type | Method and Description |
---|---|
List<SDVariable> |
doDiff(List<SDVariable> i_v1)
The actual implementation for automatic differentiation.
|
Op.Type |
getOpType() |
INDArray |
noOp()
Returns the no op version
of the input
Basically when a reduce can't happen (eg: sum(0) on a row vector)
you have a no op state for a given reduction.
|
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
The name of the op
|
int |
opNum()
The number of the op (mainly for old legacy XYZ ops
like
Op ) |
String |
tensorflowName()
The opName of this function tensorflow
|
calculateOutputShape, getFinalResult, hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, opType, setFinalResult, zeroDouble, zeroFloat, zeroHalf
equals, exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, getOpType, hashCode, init, isExecSpecial, isPassThrough, n, numProcessed, outputVariables, setN, setX, setY, setZ, toCustomOp, toString, x, y, z
arg, args, asProperties, attributeAdaptersForFunction, configFieldName, diff, dup, f, getValue, hasPlaceHolderInputs, isConfigProperties, larg, mappingsForFunction, onnxNames, outputVariables, propertiesForFunction, rarg, resolvePropertiesFromSameDiffBeforeExecution, setInstanceId, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, init, isExecSpecial, isPassThrough, n, numProcessed, setExtraArgs, setN, setX, setY, setZ, toCustomOp, x, y, z
public NormMax(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
public NormMax(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
public NormMax()
public NormMax(INDArray x)
public INDArray noOp()
Accumulation
noOp
in interface Accumulation
noOp
in class BaseAccumulation
public int opNum()
DifferentialFunction
Op
)opNum
in interface Op
opNum
in class DifferentialFunction
public String opName()
DifferentialFunction
opName
in interface Op
opName
in class DifferentialFunction
public List<SDVariable> doDiff(List<SDVariable> i_v1)
DifferentialFunction
doDiff
in class DifferentialFunction
public String onnxName()
DifferentialFunction
onnxName
in class DifferentialFunction
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DifferentialFunction
public Op.Type getOpType()
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