public class NormMax extends BaseReduceFloatOp
isComplex, isEmptyReduce, keepDims
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
Constructor and Description |
---|
NormMax() |
NormMax(INDArray x,
boolean keepDims,
int... dimensions) |
NormMax(INDArray x,
INDArray z,
int... dimensions) |
NormMax(INDArray x,
int... dimensions) |
NormMax(SameDiff sameDiff,
SDVariable i_v,
boolean keepDims,
int[] dimensions) |
NormMax(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
int[] dimensions) |
Modifier and Type | Method and Description |
---|---|
List<SDVariable> |
doDiff(List<SDVariable> grad)
The actual implementation for automatic differentiation.
|
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
|
calculateOutputDataTypes, calculateOutputShape, calculateOutputShape, getOpType, opType, resultType, resultType, validateDataTypes
hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, setDimensions
clearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, outputVariables, setX, setY, setZ, toCustomOp, toString, x, y, z
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
dimensions, getFinalResult, isComplexAccumulation, isKeepDims, setDimensions
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z
public NormMax(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
public NormMax(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
public NormMax()
public NormMax(INDArray x, int... dimensions)
public NormMax(INDArray x, boolean keepDims, int... dimensions)
public INDArray noOp()
ReduceOp
noOp
in interface ReduceOp
noOp
in class BaseReduceOp
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> grad)
DifferentialFunction
doDiff
in class DifferentialFunction
public String onnxName()
DifferentialFunction
public String tensorflowName()
DifferentialFunction
tensorflowName
in class BaseOp
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