Package org.nd4j.linalg.api.ops.impl.scalar.comparison

Class ScalarAnd

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

org.nd4j.linalg.api.ops.BaseScalarBoolOp

org.nd4j.linalg.api.ops.impl.scalar.comparison.ScalarAnd

All Implemented Interfaces:

Op, ScalarOp

public class ScalarAnd
extends BaseScalarBoolOp

Return a binary (0 or 1) when greater than a number

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.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
ScalarAnd()
ScalarAnd(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarAnd(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarAnd(INDArray x, Number num)

Method Summary

Modifier and Type	Method	Description
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)

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

calculateOutputDataTypes, calculateOutputShape, calculateOutputShape, getDimension, getOpType, opType, scalar, setDimension, setScalar, setScalar, validateDataTypes, z

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, setX, setY, setZ, tensorflowName, toCustomOp, toString, x, y

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, setX, setY, setZ, toCustomOp, x, y

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

dimensions

Constructor Detail

ScalarAnd

public ScalarAnd()

ScalarAnd

public ScalarAnd(INDArray x,
                 Number num)

ScalarAnd

public ScalarAnd(SameDiff sameDiff,
                 SDVariable i_v,
                 Number scalar)

ScalarAnd

public ScalarAnd(SameDiff sameDiff,
                 SDVariable i_v,
                 Number scalar,
                 boolean inPlace)

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

onnxName

public String onnxName()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Overrides:

onnxName in class BaseOp

Returns:

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: