org.nd4j.linalg.api.ops.impl.accum

Class SquaredNorm

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.accum.BaseReduction

org.nd4j.linalg.api.ops.impl.accum.SquaredNorm

All Implemented Interfaces:

CustomOp

public class SquaredNorm
extends BaseReduction

Squared norm (sum_i x_i^2) reduction operation

Author:

Alex Black

Nested Class Summary

Nested classes/interfaces inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp

DynamicCustomOp.DynamicCustomOpsBuilder, DynamicCustomOp.SameDiffBuilder

Field Summary

Fields inherited from class org.nd4j.linalg.api.ops.impl.accum.BaseReduction

dimensions, keepDims

Fields inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp

iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments

Fields inherited from class org.nd4j.autodiff.functions.DifferentialFunction

extraArgs, inPlace, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
SquaredNorm()
SquaredNorm(INDArray input, INDArray output, boolean keepDims, int... dimensions)
SquaredNorm(SameDiff sameDiff, SDVariable input, boolean keepDims, int... dimensions)

Method Summary

Modifier and Type	Method and Description
List<SDVariable>	doDiff(List<SDVariable> grad) The actual implementation for automatic differentiation.
String	opName() This method returns op opName as string

Methods inherited from class org.nd4j.linalg.api.ops.impl.accum.BaseReduction

addArgs

Methods inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp

addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, asProperties, assertValidForExecution, builder, calculateOutputShape, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, initFromOnnx, initFromTensorFlow, inputArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, populateInputsAndOutputsFromSameDiff, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, sameDiffBuilder, setInputArgument, setOutputArgument, tArgs, tensorflowName, toString

Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, f, getNumOutputs, getValue, hashCode, hasPlaceHolderInputs, isConfigProperties, larg, mappingsForFunction, onnxNames, outputVariable, outputVariablesNames, propertiesForFunction, rarg, resolvePropertiesFromSameDiffBeforeExecution, setInstanceId, setValueFor, tensorflowNames

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.nd4j.linalg.api.ops.CustomOp

isInplaceCall

Constructor Detail

SquaredNorm

public SquaredNorm(SameDiff sameDiff,
                   SDVariable input,
                   boolean keepDims,
                   int... dimensions)

SquaredNorm

public SquaredNorm(INDArray input,
                   INDArray output,
                   boolean keepDims,
                   int... dimensions)

SquaredNorm

public SquaredNorm()

Method Detail

opName

public String opName()

Description copied from class: DynamicCustomOp

This method returns op opName as string

Specified by:

opName in interface CustomOp

Specified by:

opName in class BaseReduction

Returns:

doDiff

public List<SDVariable> doDiff(List<SDVariable> grad)

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class DynamicCustomOp

Returns: