bias, biasCorrected, mean
dimensionVariable, isComplex, isEmptyReduce, keepDims
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
Constructor and Description |
---|
StandardDeviation() |
StandardDeviation(boolean biasCorrected) |
StandardDeviation(double mean) |
StandardDeviation(double mean,
double bias) |
StandardDeviation(double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(INDArray x) |
StandardDeviation(INDArray x,
boolean biasCorrected,
boolean keepDims,
int... dimension) |
StandardDeviation(INDArray x,
boolean keepDims,
double mean,
double bias,
boolean biasCorrected,
int... dimensions) |
StandardDeviation(INDArray x,
boolean keepDims,
double mean,
double bias,
int... dimensions) |
StandardDeviation(INDArray x,
boolean keepDims,
double mean,
int... dimensions) |
StandardDeviation(INDArray x,
boolean biasCorrected,
int... dimension) |
StandardDeviation(INDArray x,
double mean,
double bias,
boolean biasCorrected,
int... dimensions) |
StandardDeviation(INDArray x,
double mean,
double bias,
int... dimensions) |
StandardDeviation(INDArray x,
double mean,
int... dimensions) |
StandardDeviation(INDArray x,
INDArray z,
boolean newFormat,
boolean keepDims,
int[] dimensions) |
StandardDeviation(INDArray x,
INDArray z,
boolean biasCorrected,
int... dimension) |
StandardDeviation(INDArray x,
INDArray y,
double mean,
double bias,
boolean biasCorrected,
int... dimensions) |
StandardDeviation(INDArray x,
INDArray y,
double mean,
double bias,
int... dimensions) |
StandardDeviation(INDArray x,
INDArray y,
double mean,
int... dimensions) |
StandardDeviation(INDArray x,
INDArray y,
INDArray z,
boolean keepDims,
int[] dimensions,
double mean) |
StandardDeviation(INDArray x,
INDArray y,
INDArray z,
boolean keepDims,
int[] dimensions,
double mean,
double bias) |
StandardDeviation(INDArray x,
INDArray y,
INDArray z,
boolean keepDims,
int[] dimensions,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(INDArray x,
INDArray y,
INDArray z,
double mean,
double bias,
boolean biasCorrected,
int... dimensions) |
StandardDeviation(INDArray x,
INDArray y,
INDArray z,
double mean,
double bias,
int... dimensions) |
StandardDeviation(INDArray x,
INDArray y,
INDArray z,
double mean,
int... dimensions) |
StandardDeviation(INDArray x,
int... dimension) |
StandardDeviation(SameDiff sameDiff,
double mean) |
StandardDeviation(SameDiff sameDiff,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
boolean biasCorrected,
boolean keepDims,
int[] dimensions) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
boolean keepDims,
double mean) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
boolean keepDims,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
boolean keepDims,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
double mean) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
int[] dimensions,
boolean keepDims,
double mean) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
int[] dimensions,
boolean keepDims,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
int[] dimensions,
boolean keepDims,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
int[] dimensions,
double mean) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
int[] dimensions,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
int[] dimensions,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable dimensions,
boolean keepDims,
double mean) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable dimensions,
boolean keepDims,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable dimensions,
boolean keepDims,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
double mean) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
int[] dimensions,
boolean keepDims,
double mean) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
int[] dimensions,
boolean keepDims,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
int[] dimensions,
boolean keepDims,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
int[] dimensions,
double mean) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
int[] dimensions,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
int[] dimensions,
double mean,
double bias,
boolean biasCorrected) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
SDVariable dimensions,
double mean) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
SDVariable dimensions,
double mean,
double bias) |
StandardDeviation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
SDVariable dimensions,
double mean,
double bias,
boolean biasCorrected) |
Modifier and Type | Method and Description |
---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> dataTypes)
Calculate the data types for the output arrays.
|
List<LongShapeDescriptor> |
calculateOutputShape()
Calculate the output shape for this op
|
List<SDVariable> |
doDiff(List<SDVariable> grad)
The actual implementation for automatic differentiation.
|
Op.Type |
getOpType() |
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 ) |
Op.Type |
opType()
The type of the op
|
void |
setPropertiesForFunction(Map<String,Object> properties) |
String |
tensorflowName()
The opName of this function tensorflow
|
calculateOutputShape, isBiasCorrected, noOp, resultType, resultType, setBiasCorrected, validateDataTypes
configureWithSameDiff, hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, setDimensions
clearArrays, computeVariables, 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, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
dimensions, getFinalResult
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, boolean biasCorrected, boolean keepDims, int[] dimensions)
public StandardDeviation(INDArray x, boolean biasCorrected, boolean keepDims, int... dimension)
public StandardDeviation(INDArray x, boolean biasCorrected, int... dimension)
public StandardDeviation()
public StandardDeviation(boolean biasCorrected)
public StandardDeviation(INDArray x, int... dimension)
public StandardDeviation(INDArray x)
public StandardDeviation(INDArray x, INDArray z, boolean biasCorrected, int... dimension)
public StandardDeviation(INDArray x, INDArray z, boolean newFormat, boolean keepDims, int[] dimensions)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, int[] dimensions, boolean keepDims, double mean)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, boolean keepDims, double mean)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, double mean)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, int[] dimensions, double mean)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, double mean)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, boolean keepDims, double mean)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable dimensions, boolean keepDims, double mean)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, double mean)
public StandardDeviation(double mean)
public StandardDeviation(INDArray x, INDArray y, INDArray z, boolean keepDims, int[] dimensions, double mean)
public StandardDeviation(INDArray x, double mean, int... dimensions)
public StandardDeviation(INDArray x, boolean keepDims, double mean, int... dimensions)
public StandardDeviation(INDArray x, INDArray y, INDArray z, double mean, int... dimensions)
public StandardDeviation(SameDiff sameDiff, double mean)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions, double mean)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, int[] dimensions, boolean keepDims, double mean, double bias)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, boolean keepDims, double mean, double bias)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, double mean, double bias)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, int[] dimensions, double mean, double bias)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, double mean, double bias)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, boolean keepDims, double mean, double bias)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable dimensions, boolean keepDims, double mean, double bias)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, double mean, double bias)
public StandardDeviation(double mean, double bias)
public StandardDeviation(INDArray x, INDArray y, INDArray z, boolean keepDims, int[] dimensions, double mean, double bias)
public StandardDeviation(INDArray x, double mean, double bias, int... dimensions)
public StandardDeviation(INDArray x, boolean keepDims, double mean, double bias, int... dimensions)
public StandardDeviation(INDArray x, INDArray y, double mean, double bias, int... dimensions)
public StandardDeviation(INDArray x, INDArray y, INDArray z, double mean, double bias, int... dimensions)
public StandardDeviation(SameDiff sameDiff, double mean, double bias)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions, double mean, double bias)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, int[] dimensions, boolean keepDims, double mean, double bias, boolean biasCorrected)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, boolean keepDims, double mean, double bias, boolean biasCorrected)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, double mean, double bias, boolean biasCorrected)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, int[] dimensions, double mean, double bias, boolean biasCorrected)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, double mean, double bias, boolean biasCorrected)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, boolean keepDims, double mean, double bias, boolean biasCorrected)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable dimensions, boolean keepDims, double mean, double bias, boolean biasCorrected)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, double mean, double bias, boolean biasCorrected)
public StandardDeviation(double mean, double bias, boolean biasCorrected)
public StandardDeviation(INDArray x, INDArray y, INDArray z, boolean keepDims, int[] dimensions, double mean, double bias, boolean biasCorrected)
public StandardDeviation(INDArray x, double mean, double bias, boolean biasCorrected, int... dimensions)
public StandardDeviation(INDArray x, boolean keepDims, double mean, double bias, boolean biasCorrected, int... dimensions)
public StandardDeviation(INDArray x, INDArray y, double mean, double bias, boolean biasCorrected, int... dimensions)
public StandardDeviation(INDArray x, INDArray y, INDArray z, double mean, double bias, boolean biasCorrected, int... dimensions)
public StandardDeviation(SameDiff sameDiff, double mean, double bias, boolean biasCorrected)
public StandardDeviation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions, double mean, double bias, boolean biasCorrected)
public int opNum()
DifferentialFunction
Op
)public String opName()
DifferentialFunction
public String onnxName()
DifferentialFunction
public String tensorflowName()
DifferentialFunction
tensorflowName
in class Variance
public Op.Type getOpType()
public Op.Type opType()
DifferentialFunction
public void setPropertiesForFunction(Map<String,Object> properties)
setPropertiesForFunction
in class BaseReduceOp
public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes)
DifferentialFunction
DifferentialFunction.calculateOutputShape()
, this method differs in that it does not
require the input arrays to be populated.
This is important as it allows us to do greedy datatype inference for the entire net - even if arrays are not
available.calculateOutputDataTypes
in class Variance
dataTypes
- The data types of the inputspublic List<SDVariable> doDiff(List<SDVariable> grad)
DifferentialFunction
public List<LongShapeDescriptor> calculateOutputShape()
DifferentialFunction
calculateOutputShape
in class Variance
Copyright © 2022. All rights reserved.