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

Class Histogram

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.Histogram

All Implemented Interfaces:

Op, TransformOp

public class Histogram
extends BaseTransformOp

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
Histogram()
Histogram(INDArray x, INDArray z)
Histogram(INDArray x, int numberOfBins)
Histogram(SameDiff sameDiff)
Histogram(SameDiff sameDiff, SDVariable i_v, boolean inPlace, int numBins)
Histogram(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, int numBins)
Histogram(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, int numBins)

Method Summary

Modifier and Type	Method and Description
List<SDVariable>	doDiff(List<SDVariable> f1) The actual implementation for automatic differentiation.
void	initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph) Iniitialize the function from the given OnnxProto3.NodeProto
void	initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph) Initialize the function from the given NodeDef
boolean	isExecSpecial() Whether the executioner needs to do a special call or not
Map<String,Map<String,PropertyMapping>>	mappingsForFunction() Returns the mappings for a given function ( for tensorflow and onnx import mapping properties of this function).
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.BaseTransformOp

calculateOutputShape, opType, z

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

equals, exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, getOpType, hashCode, init, isPassThrough, n, numProcessed, outputVariables, setN, setX, setY, setZ, toCustomOp, toString, x, y

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

arg, args, asProperties, attributeAdaptersForFunction, configFieldName, diff, dup, f, getValue, hasPlaceHolderInputs, isConfigProperties, larg, 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, isPassThrough, n, numProcessed, setExtraArgs, setN, setX, setY, setZ, toCustomOp, x, y

Constructor Detail

Histogram

public Histogram(SameDiff sameDiff,
                 SDVariable i_v,
                 boolean inPlace,
                 int numBins)

Histogram

public Histogram(SameDiff sameDiff,
                 SDVariable i_v,
                 int[] shape,
                 boolean inPlace,
                 Object[] extraArgs,
                 int numBins)

Histogram

public Histogram(SameDiff sameDiff,
                 SDVariable i_v,
                 Object[] extraArgs,
                 int numBins)

Histogram

public Histogram()

Histogram

public Histogram(INDArray x,
                 INDArray z)

Histogram

public Histogram(INDArray x,
                 int numberOfBins)

Histogram

public Histogram(SameDiff sameDiff)

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:

initFromTensorFlow

public void initFromTensorFlow(NodeDef nodeDef,
                               SameDiff initWith,
                               Map<String,AttrValue> attributesForNode,
                               GraphDef graph)

Description copied from class: DifferentialFunction

Initialize the function from the given NodeDef

Overrides:

initFromTensorFlow in class BaseOp

initFromOnnx

public void initFromOnnx(OnnxProto3.NodeProto node,
                         SameDiff initWith,
                         Map<String,OnnxProto3.AttributeProto> attributesForNode,
                         OnnxProto3.GraphProto graph)

Description copied from class: DifferentialFunction

Iniitialize the function from the given OnnxProto3.NodeProto

Overrides:

initFromOnnx in class BaseOp

mappingsForFunction

public Map<String,Map<String,PropertyMapping>> mappingsForFunction()

Description copied from class: DifferentialFunction

Returns the mappings for a given function ( for tensorflow and onnx import mapping properties of this function). The mapping is indexed by field name. If the function has no properties, this returned map will be empty. Note that some functions have multiple names. This function returns a map indexed by each alias it has for a given name. These names include both onnx and tensorflow names (which might be 1 or more)

Overrides:

mappingsForFunction 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

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:

isExecSpecial

public boolean isExecSpecial()

Description copied from interface: Op

Whether the executioner needs to do a special call or not

Specified by:

isExecSpecial in interface Op

Overrides:

isExecSpecial in class BaseOp

Returns:

true if the executioner needs to do a special call or not 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: