public class SquaredNorm extends BaseReduceFloatOp
isComplex, isEmptyReduce, keepDims
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
Constructor and Description |
---|
SquaredNorm() |
SquaredNorm(INDArray input,
boolean keepDims,
int... dimensions) |
SquaredNorm(INDArray input,
INDArray output,
boolean keepDims,
int... dimensions) |
SquaredNorm(INDArray x,
int... dimensions) |
SquaredNorm(SameDiff sameDiff,
SDVariable input,
boolean keepDims,
int... dimensions) |
Modifier and Type | Method and Description |
---|---|
List<SDVariable> |
doDiff(List<SDVariable> grad)
The actual implementation for automatic differentiation.
|
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, noOp, 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, noOp, setDimensions
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z
public SquaredNorm(SameDiff sameDiff, SDVariable input, boolean keepDims, int... dimensions)
public SquaredNorm(INDArray input, INDArray output, boolean keepDims, int... dimensions)
public SquaredNorm(INDArray input, boolean keepDims, int... dimensions)
public SquaredNorm()
public SquaredNorm(INDArray x, int... dimensions)
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 String onnxName()
DifferentialFunction
public String tensorflowName()
DifferentialFunction
tensorflowName
in class BaseOp
public List<SDVariable> doDiff(List<SDVariable> grad)
DifferentialFunction
doDiff
in class DifferentialFunction
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