org.nd4j.linalg.api.ops.impl.accum

Class Bias

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.BaseOp

org.nd4j.linalg.api.ops.BaseAccumulation

org.nd4j.linalg.api.ops.impl.accum.Bias

All Implemented Interfaces:

Accumulation, Op

public class Bias
extends BaseAccumulation

Calculate a bias

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.BaseAccumulation

finalResult, isComplex, keepDims, newFormat

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
Bias()
Bias(INDArray x)
Bias(INDArray x, INDArray y)
Bias(INDArray x, INDArray y, INDArray z, long n)
Bias(INDArray x, INDArray y, long n)
Bias(SameDiff sameDiff, SDVariable i_v, int[] dimensions, double mean)
Bias(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, double mean)

Method Summary

Modifier and Type	Method and Description
List<SDVariable>	doDiff(List<SDVariable> f1) The actual implementation for automatic differentiation.
Op.Type	getOpType()
boolean	isPassThrough() Returns whether the op should be executed or not (through the executioner)
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)
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.BaseAccumulation

calculateOutputShape, getFinalResult, hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, noOp, opType, setFinalResult, zeroDouble, zeroFloat, zeroHalf

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

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

Constructor Detail

Bias

public Bias(SameDiff sameDiff,
            SDVariable i_v,
            int[] dimensions,
            double mean)

Bias

public Bias(SameDiff sameDiff,
            SDVariable i_v,
            SDVariable i_v2,
            int[] dimensions,
            double mean)

Bias

public Bias()

Bias

public Bias(INDArray x,
            INDArray y,
            INDArray z,
            long n)

Bias

public Bias(INDArray x,
            INDArray y,
            long n)

Bias

public Bias(INDArray x)

Bias

public Bias(INDArray x,
            INDArray y)

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

isPassThrough

public boolean isPassThrough()

Description copied from interface: Op

Returns whether the op should be executed or not (through the executioner)

Specified by:

isPassThrough in interface Op

Overrides:

isPassThrough in class BaseOp

Returns:

true if the op is pass through false otherwise

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:

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:

getOpType

public Op.Type getOpType()