org.nd4j.linalg.api.ops.impl.transforms

Class MaxOut

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

org.nd4j.linalg.api.ops.BaseTransformOp

org.nd4j.linalg.api.ops.impl.transforms.MaxOut

All Implemented Interfaces:

Op, TransformOp

public class MaxOut
extends BaseTransformOp

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 and Description
MaxOut()
MaxOut(INDArray x)
MaxOut(INDArray x, INDArray z)
MaxOut(SameDiff sameDiff, SDVariable i_v, boolean inPlace, Number max)
MaxOut(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, Number max)

Method Summary

Modifier and Type	Method and Description
List<LongShapeDescriptor>	calculateOutputShape() Calculate the output shape for this op
List<SDVariable>	doDiff(List<SDVariable> f1) The actual implementation for automatic differentiation.
Op.Type	getOpType()
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)
DataType	resultType() This method returns datatype for result array wrt given inputs
DataType	resultType(OpContext oc)
String	tensorflowName() The opName of this function tensorflow
boolean	validateDataTypes(OpContext oc, boolean experimentalMode)

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

z

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

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

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

arg, arg, argNames, args, attributeAdaptersForFunction, calculateOutputDataTypes, calculateOutputShape, configFieldName, diff, dup, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, opType, 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

Constructor Detail

MaxOut

public MaxOut(SameDiff sameDiff,
              SDVariable i_v,
              boolean inPlace,
              Number max)

MaxOut

public MaxOut(SameDiff sameDiff,
              SDVariable i_v,
              Object[] extraArgs,
              Number max)

MaxOut

public MaxOut()

MaxOut

public MaxOut(INDArray x,
              INDArray z)

MaxOut

public MaxOut(INDArray x)

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:

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> f1)

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Specified by:

doDiff in class DifferentialFunction

Returns:

resultType

public DataType resultType()

Description copied from interface: TransformOp

This method returns datatype for result array wrt given inputs

Returns:

resultType

public DataType resultType(OpContext oc)

getOpType

public Op.Type getOpType()

validateDataTypes

public boolean validateDataTypes(OpContext oc,
                                 boolean experimentalMode)

calculateOutputShape

public List<LongShapeDescriptor> calculateOutputShape()

Description copied from class: DifferentialFunction

Calculate the output shape for this op

Specified by:

calculateOutputShape in class BaseTransformOp

Returns:

List of output shape descriptors