org.nd4j.linalg.api.ops.random.custom

Class RandomBernoulli

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.random.custom.RandomBernoulli

All Implemented Interfaces:

CustomOp

public class RandomBernoulli
extends DynamicCustomOp

Random bernoulli distribution: p(x=1) = p, p(x=0) = 1-p i.e., output is 0 or 1 with probability p.

Author:

Alex Black

Nested Class Summary

Nested classes/interfaces inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp

DynamicCustomOp.DynamicCustomOpsBuilder, DynamicCustomOp.SameDiffBuilder

Field Summary

Fields inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp

iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments

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

dimensions, extraArgs, inPlace, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
RandomBernoulli()
RandomBernoulli(INDArray shape, INDArray out, double p)
RandomBernoulli(SameDiff sd, SDVariable shape, double p)

Method Summary

Modifier and Type	Method and Description
List<SDVariable>	doDiff(List<SDVariable> gradients) The actual implementation for automatic differentiation.
String	opName() This method returns op opName as string

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

addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, builder, calculateOutputShape, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, initFromOnnx, initFromTensorFlow, inputArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, populateInputsAndOutputsFromSameDiff, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, sameDiffBuilder, setInputArgument, setOutputArgument, tArgs, tensorflowName, toString

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

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, f, getNumOutputs, getValue, hashCode, hasPlaceHolderInputs, isConfigProperties, larg, mappingsForFunction, onnxNames, outputVariable, outputVariablesNames, propertiesForFunction, rarg, resolvePropertiesFromSameDiffBeforeExecution, 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.CustomOp

isInplaceCall

Constructor Detail

RandomBernoulli

public RandomBernoulli()

RandomBernoulli

public RandomBernoulli(SameDiff sd,
                       SDVariable shape,
                       double p)

RandomBernoulli

public RandomBernoulli(INDArray shape,
                       INDArray out,
                       double p)

Method Detail

opName

public String opName()

Description copied from class: DynamicCustomOp

This method returns op opName as string

Specified by:

opName in interface CustomOp

Overrides:

opName in class DynamicCustomOp

Returns:

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class DynamicCustomOp

Returns: