org.nd4j.linalg.api.ops.impl.reduce.floating

Class Norm1

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

org.nd4j.linalg.api.ops.BaseReduceOp

org.nd4j.linalg.api.ops.BaseReduceFloatOp

org.nd4j.linalg.api.ops.impl.reduce.floating.Norm1

All Implemented Interfaces:

Op, ReduceFloatOp, ReduceOp

public class Norm1
extends BaseReduceFloatOp

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.BaseReduceOp

isComplex, isEmptyReduce, keepDims

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

dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId

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

dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
Norm1()
Norm1(INDArray x, boolean keepDims, int... dimensions)
Norm1(INDArray x, INDArray z, int... dimensions)
Norm1(INDArray x, int... dimensions)
Norm1(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)

Method Summary

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

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

calculateOutputDataTypes, calculateOutputShape, calculateOutputShape, getOpType, opType, resultType, resultType, validateDataTypes

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

hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, setDimensions

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

clearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, outputVariables, setX, setY, setZ, toCustomOp, toString, x, y, z

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

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, 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.ReduceOp

dimensions, getFinalResult, isComplexAccumulation, isKeepDims, setDimensions

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

clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z

Constructor Detail

Norm1

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

Norm1

public Norm1()

Norm1

public Norm1(INDArray x,
             INDArray z,
             int... dimensions)

Norm1

public Norm1(INDArray x,
             int... dimensions)

Norm1

public Norm1(INDArray x,
             boolean keepDims,
             int... dimensions)

Method Detail

noOp

public INDArray noOp()

Description copied from interface: ReduceOp

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 ReduceOp

Overrides:

noOp in class BaseReduceOp

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

Overrides:

onnxName in class BaseOp

Returns:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowName in class BaseOp

Returns:

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Specified by:

doDiff in class DifferentialFunction

Returns: