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

Class BaseRandomOp

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

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

All Implemented Interfaces:

Op, RandomOp

Direct Known Subclasses:

AlphaDropOut, BernoulliDistribution, BinomialDistribution, BinomialDistributionEx, Choice, DropOut, DropOutInverted, GaussianDistribution, Linspace, LogNormalDistribution, ProbablisticMerge, TruncatedNormalDistribution, UniformDistribution

public abstract class BaseRandomOp
extends BaseOp
implements RandomOp

Nested Class Summary

Nested classes/interfaces inherited from interface org.nd4j.linalg.api.ops.Op

Op.Type

Field Summary

Fields

Modifier and Type	Field	Description
protected DataType	dataType
protected long[]	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
BaseRandomOp(SameDiff sd, long[] shape)
BaseRandomOp(SameDiff sameDiff, SDVariable i_v)
BaseRandomOp(INDArray x, INDArray y, INDArray z)

Method Summary

Modifier and Type	Method	Description
List<DataType>	calculateOutputDataTypes(List<DataType> inputDataTypes)	Calculate the data types for the output arrays.
List<LongShapeDescriptor>	calculateOutputShape()	Calculate the output shape for this op
boolean	isInPlace()
boolean	isTripleArgRngOp()
Op.Type	opType()	The type of the op

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, onnxName, outputVariables, setX, setY, setZ, tensorflowName, toCustomOp, toString, x, y, z

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

arg, arg, argNames, args, attributeAdaptersForFunction, calculateOutputShape, configFieldName, configureWithSameDiff, diff, doDiff, dup, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, opName, opNum, 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, opName, opNum, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z

Field Detail

shape

protected long[] shape

dataType

protected DataType dataType

Constructor Detail

BaseRandomOp

public BaseRandomOp(SameDiff sameDiff,
                    SDVariable i_v)

BaseRandomOp

public BaseRandomOp(SameDiff sd,
                    long[] shape)

BaseRandomOp

public BaseRandomOp(INDArray x,
                    INDArray y,
                    INDArray z)

Method Detail

opType

public Op.Type opType()

Description copied from class: DifferentialFunction

The type of the op

Overrides:

opType in class DifferentialFunction

Returns:

calculateOutputShape

public List<LongShapeDescriptor> calculateOutputShape()

Description copied from class: DifferentialFunction

Calculate the output shape for this op

Overrides:

calculateOutputShape in class DifferentialFunction

Returns:

List of output shape descriptors

calculateOutputDataTypes

public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes)

Description copied from class: DifferentialFunction

Calculate the data types for the output arrays. Though datatypes can also be inferred from DifferentialFunction.calculateOutputShape(), this method differs in that it does not require the input arrays to be populated. This is important as it allows us to do greedy datatype inference for the entire net - even if arrays are not available.

Overrides:

calculateOutputDataTypes in class DifferentialFunction

Parameters:

inputDataTypes - The data types of the inputs

Returns:

The data types of the outputs

isInPlace

public boolean isInPlace()

isTripleArgRngOp

public boolean isTripleArgRngOp()