Package org.nd4j.linalg.api.ops.random.impl

Class Linspace

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

org.nd4j.linalg.api.ops.random.BaseRandomOp

org.nd4j.linalg.api.ops.random.impl.Linspace

All Implemented Interfaces:

Op, RandomOp

public class Linspace
extends BaseRandomOp

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.random.BaseRandomOp

dataType, shape

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	Description
Linspace()
Linspace(double from, double to, long length, DataType dataType)
Linspace(double from, long length, double step, DataType dataType)
Linspace(@NonNull INDArray z, double from, double to)
Linspace(@NonNull INDArray z, double from, double to, double step)
Linspace(SameDiff sd, double from, double to, long length)

Method Summary

Modifier and Type	Method	Description
List<LongShapeDescriptor>	calculateOutputShape()	Calculate the output shape for this op
List<LongShapeDescriptor>	calculateOutputShape(OpContext oc)
List<SDVariable>	doDiff(List<SDVariable> f1)	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)
void	setX(INDArray x)	set x (the input ndarray)
void	setY(INDArray y)	set y(the pairwise ndarray)
String	tensorflowName()	The opName of this function tensorflow
INDArray	x()	The origin ndarray
INDArray	y()	The pairwise op ndarray

Methods inherited from class org.nd4j.linalg.api.ops.random.BaseRandomOp

calculateOutputDataTypes, isInPlace, isTripleArgRngOp, opType

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

clearArrays, computeVariables, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, initFromOnnx, initFromTensorFlow, outputVariables, setZ, toCustomOp, toString, z

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

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, configureWithSameDiff, diff, dup, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, 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.Op

clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setZ, toCustomOp, z

Constructor Detail

Linspace

public Linspace()

Linspace

public Linspace(double from,
                long length,
                double step,
                DataType dataType)

Linspace

public Linspace(double from,
                double to,
                long length,
                DataType dataType)

Linspace

public Linspace(@NonNull
                @NonNull INDArray z,
                double from,
                double to)

Linspace

public Linspace(@NonNull
                @NonNull INDArray z,
                double from,
                double to,
                double step)

Linspace

public Linspace(SameDiff sd,
                double from,
                double to,
                long length)

Method Detail

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

x

public INDArray x()

Description copied from interface: Op

The origin ndarray

Specified by:

x in interface Op

Overrides:

x in class BaseOp

Returns:

the origin ndarray

y

public INDArray y()

Description copied from interface: Op

The pairwise op ndarray

Specified by:

y in interface Op

Overrides:

y in class BaseOp

Returns:

the pairwise op ndarray

setX

public void setX(INDArray x)

Description copied from interface: Op

set x (the input ndarray)

Specified by:

setX in interface Op

Overrides:

setX in class BaseOp

setY

public void setY(INDArray y)

Description copied from interface: Op

set y(the pairwise ndarray)

Specified by:

setY in interface Op

Overrides:

setY in class BaseOp

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:

calculateOutputShape

public List<LongShapeDescriptor> calculateOutputShape(OpContext oc)

Overrides:

calculateOutputShape in class DifferentialFunction

calculateOutputShape

public List<LongShapeDescriptor> calculateOutputShape()

Description copied from class: DifferentialFunction

Calculate the output shape for this op

Overrides:

calculateOutputShape in class BaseRandomOp

Returns:

List of output shape descriptors

doDiff

public List<SDVariable> doDiff(List<SDVariable> f1)

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Specified by:

doDiff in class DifferentialFunction

Returns: