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

Class Norm1

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

org.nd4j.linalg.api.ops.BaseAccumulation

org.nd4j.linalg.api.ops.impl.accum.Norm1

All Implemented Interfaces:

Accumulation, Op

public class Norm1
extends BaseAccumulation

Sum of absolute values

Author:

Adam Gibson

Nested Class Summary

Nested classes/interfaces inherited from interface org.nd4j.linalg.api.ops.Op

Op.Type

Field Summary

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

finalResult, isComplex, keepDims, newFormat

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

extraArgs, extraArgz, n, numProcessed, passThrough, x, xVertexId, y, yVertexId, z, zVertexId

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

dimensions, inPlace, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
Norm1()
Norm1(INDArray x)
Norm1(INDArray x, INDArray y)
Norm1(INDArray x, INDArray y, INDArray z, long n)
Norm1(INDArray x, INDArray y, long n)
Norm1(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
Norm1(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)

Method Summary

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

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

calculateOutputShape, getFinalResult, hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, opType, setFinalResult, zeroDouble, zeroFloat, zeroHalf

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

equals, exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, getOpType, hashCode, init, isExecSpecial, isPassThrough, n, numProcessed, outputVariables, setN, setX, setY, setZ, toCustomOp, toString, x, y, z

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

arg, args, asProperties, attributeAdaptersForFunction, configFieldName, diff, dup, f, getValue, hasPlaceHolderInputs, isConfigProperties, larg, mappingsForFunction, onnxNames, outputVariables, 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.Op

exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, init, isExecSpecial, isPassThrough, n, numProcessed, setExtraArgs, setN, setX, setY, setZ, toCustomOp, x, y, z

Constructor Detail

Norm1

public Norm1(SameDiff sameDiff,
             SDVariable i_v,
             int[] dimensions)

Norm1

public Norm1(SameDiff sameDiff,
             SDVariable i_v,
             SDVariable i_v2,
             int[] dimensions)

Norm1

public Norm1()

Norm1

public Norm1(INDArray x,
             INDArray y,
             INDArray z,
             long n)

Norm1

public Norm1(INDArray x,
             INDArray y,
             long n)

Norm1

public Norm1(INDArray x)

Norm1

public Norm1(INDArray x,
             INDArray y)

Method Detail

noOp

public INDArray noOp()

Description copied from interface: Accumulation

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. For most accumulations, this should return x but certain transformations should return say: the absolute value

Specified by:

noOp in interface Accumulation

Overrides:

noOp in class BaseAccumulation

Returns:

the no op version of the input

opNum

public int opNum()

Description copied from class: DifferentialFunction

The number of the op (mainly for old legacy XYZ ops like Op)

Specified by:

opNum in interface Op

Overrides:

opNum in class DifferentialFunction

Returns:

opName

public String opName()

Description copied from class: DifferentialFunction

The name of the op

Specified by:

opName in interface Op

Overrides:

opName in class DifferentialFunction

Returns:

the opName of this operation

onnxName

public String onnxName()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Specified by:

onnxName in class DifferentialFunction

Returns:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Specified by:

tensorflowName in class DifferentialFunction

Returns:

doDiff

public List<SDVariable> doDiff(List<SDVariable> i_v1)

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Specified by:

doDiff in class DifferentialFunction

Returns:

getOpType

public Op.Type getOpType()