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

Class DropOut

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.DropOut

All Implemented Interfaces:

Op, RandomOp

public class DropOut
extends BaseRandomOp

Inverted DropOut implementation as Op

Author:

raver119@gmail.com

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

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
DropOut(INDArray x, double p)
DropOut(INDArray x, INDArray z, double p)
DropOut(INDArray x, INDArray z, double p, long n)
DropOut(SameDiff sameDiff, SDVariable input, double p)

Method Summary

Modifier and Type	Method and Description
List<SDVariable>	doDiff(List<SDVariable> f1) The actual implementation for automatic differentiation.
void	init(INDArray x, INDArray y, INDArray z, long n) Initialize the operation based on the parameters
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)
Op.Type	opType() The type of the op
Map<String,Object>	propertiesForFunction() Returns the properties for a given function
String	tensorflowName() The opName of this function tensorflow

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

calculateOutputShape

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

equals, exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, getOpType, hashCode, initFromOnnx, initFromTensorFlow, 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, 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, isExecSpecial, isPassThrough, n, numProcessed, setExtraArgs, setN, setX, setY, setZ, toCustomOp, x, y, z

Constructor Detail

DropOut

public DropOut(SameDiff sameDiff,
               SDVariable input,
               double p)

DropOut

public DropOut(@NonNull
               INDArray x,
               double p)

DropOut

public DropOut(@NonNull
               INDArray x,
               @NonNull
               INDArray z,
               double p)

DropOut

public DropOut(@NonNull
               INDArray x,
               @NonNull
               INDArray z,
               double p,
               long n)

Method Detail

propertiesForFunction

public Map<String,Object> propertiesForFunction()

Description copied from class: DifferentialFunction

Returns the properties for a given function

Overrides:

propertiesForFunction in class DifferentialFunction

Returns:

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

init

public void init(INDArray x,
                 INDArray y,
                 INDArray z,
                 long n)

Description copied from interface: Op

Initialize the operation based on the parameters

Specified by:

init in interface Op

Overrides:

init in class BaseOp

Parameters:

x - the input

y - the pairwise transform ndarray

z - the resulting ndarray

n - the number of elements

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:

opType

public Op.Type opType()

Description copied from class: DifferentialFunction

The type of the op

Overrides:

opType in class BaseRandomOp

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: