Package org.nd4j.linalg.api.ops.impl.shape

Class StridedSlice

java.lang.Object

org.nd4j.autodiff.functions.DifferentialFunction

org.nd4j.linalg.api.ops.DynamicCustomOp

org.nd4j.linalg.api.ops.impl.shape.StridedSlice

All Implemented Interfaces:

CustomOp

public class StridedSlice
extends DynamicCustomOp

Nested Class Summary

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

DynamicCustomOp.DynamicCustomOpsBuilder

Field Summary

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

axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, sArguments, tArguments

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

dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor	Description
StridedSlice()
StridedSlice(SameDiff sameDiff, SDVariable in, @lombok.NonNull int[] begin, @lombok.NonNull int[] end, @lombok.NonNull int[] strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)
StridedSlice(SameDiff sameDiff, SDVariable in, @lombok.NonNull long[] begin, @lombok.NonNull long[] end, @lombok.NonNull long[] strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)
StridedSlice(SameDiff sameDiff, SDVariable in, int[] begin, int[] end, int[] strides)
StridedSlice(SameDiff sameDiff, SDVariable in, long[] begin, long[] end, long[] strides)
StridedSlice(SameDiff sd, SDVariable in, SDVariable begin, SDVariable end, SDVariable strides)
StridedSlice(SameDiff sd, SDVariable in, SDVariable begin, SDVariable end, SDVariable strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)
StridedSlice(INDArray in, int[] begin, int[] end, int[] strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)
StridedSlice(INDArray in, long[] begin, long[] end, long[] strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)
StridedSlice(INDArray in, INDArray begin, INDArray end, INDArray strides)
StridedSlice(INDArray in, INDArray begin, INDArray end, INDArray strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)

Method Summary

Modifier and Type	Method	Description
void	assertValidForExecution()	Asserts a valid state for execution, otherwise throws an ND4JIllegalStateException
List<DataType>	calculateOutputDataTypes(List<DataType> dataTypes)	Calculate the data types for the output arrays.
void	configureFromArguments()	This allows a custom op to configure relevant fields from its arguments.
List<SDVariable>	doDiff(List<SDVariable> i_v)	The actual implementation for automatic differentiation.
void	initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)	Initialize the function from the given NodeDef
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()	This method returns op opName as string
void	setPropertiesForFunction(Map<String,Object> properties)
String	tensorflowName()	The opName of this function tensorflow

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

addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addOutputsToOp, addSArgument, addTArgument, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, computeArrays, dArgs, generateFake, generateFake, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getSArgument, getTArgument, getValue, iArgs, initFromOnnx, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numSArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, propertiesForFunction, removeIArgument, removeInputArgument, removeOutputArgument, removeSArgument, removeTArgument, sArgs, setInputArgument, setInputArguments, setOutputArgument, setValueFor, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNull

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

arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, configureWithSameDiff, diff, dup, equals, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getNumOutputs, getStringFromProperty, hashCode, isConfigProperties, larg, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, 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

StridedSlice

public StridedSlice()

StridedSlice

public StridedSlice(SameDiff sameDiff,
                    SDVariable in,
                    int[] begin,
                    int[] end,
                    int[] strides)

StridedSlice

public StridedSlice(SameDiff sameDiff,
                    SDVariable in,
                    long[] begin,
                    long[] end,
                    long[] strides)

StridedSlice

public StridedSlice(SameDiff sameDiff,
                    SDVariable in,
                    @NonNull
                    @lombok.NonNull long[] begin,
                    @NonNull
                    @lombok.NonNull long[] end,
                    @NonNull
                    @lombok.NonNull long[] strides,
                    int beginMask,
                    int endMask,
                    int ellipsisMask,
                    int newAxisMask,
                    int shrinkAxisMask)

StridedSlice

public StridedSlice(SameDiff sameDiff,
                    SDVariable in,
                    @NonNull
                    @lombok.NonNull int[] begin,
                    @NonNull
                    @lombok.NonNull int[] end,
                    @NonNull
                    @lombok.NonNull int[] strides,
                    int beginMask,
                    int endMask,
                    int ellipsisMask,
                    int newAxisMask,
                    int shrinkAxisMask)

StridedSlice

public StridedSlice(INDArray in,
                    int[] begin,
                    int[] end,
                    int[] strides,
                    int beginMask,
                    int endMask,
                    int ellipsisMask,
                    int newAxisMask,
                    int shrinkAxisMask)

StridedSlice

public StridedSlice(INDArray in,
                    long[] begin,
                    long[] end,
                    long[] strides,
                    int beginMask,
                    int endMask,
                    int ellipsisMask,
                    int newAxisMask,
                    int shrinkAxisMask)

StridedSlice

public StridedSlice(SameDiff sd,
                    SDVariable in,
                    SDVariable begin,
                    SDVariable end,
                    SDVariable strides)

StridedSlice

public StridedSlice(SameDiff sd,
                    SDVariable in,
                    SDVariable begin,
                    SDVariable end,
                    SDVariable strides,
                    int beginMask,
                    int endMask,
                    int ellipsisMask,
                    int newAxisMask,
                    int shrinkAxisMask)

StridedSlice

public StridedSlice(INDArray in,
                    INDArray begin,
                    INDArray end,
                    INDArray strides)

StridedSlice

public StridedSlice(INDArray in,
                    INDArray begin,
                    INDArray end,
                    INDArray strides,
                    int beginMask,
                    int endMask,
                    int ellipsisMask,
                    int newAxisMask,
                    int shrinkAxisMask)

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:

onnxName

public String onnxName()

Description copied from class: DifferentialFunction

The opName of this function in onnx

Overrides:

onnxName in class DynamicCustomOp

Returns:

tensorflowName

public String tensorflowName()

Description copied from class: DifferentialFunction

The opName of this function tensorflow

Overrides:

tensorflowName in class DynamicCustomOp

Returns:

assertValidForExecution

public void assertValidForExecution()

Description copied from interface: CustomOp

Asserts a valid state for execution, otherwise throws an ND4JIllegalStateException

Specified by:

assertValidForExecution in interface CustomOp

Overrides:

assertValidForExecution in class DynamicCustomOp

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 DynamicCustomOp

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 DynamicCustomOp

Returns:

configureFromArguments

public void configureFromArguments()

Description copied from interface: CustomOp

This allows a custom op to configure relevant fields from its arguments. This is needed when ops are created via reflection for things like model import.

Specified by:

configureFromArguments in interface CustomOp

Overrides:

configureFromArguments in class DynamicCustomOp

setPropertiesForFunction

public void setPropertiesForFunction(Map<String,Object> properties)

Overrides:

setPropertiesForFunction in class DynamicCustomOp

doDiff

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

Description copied from class: DifferentialFunction

The actual implementation for automatic differentiation.

Overrides:

doDiff in class DynamicCustomOp

Returns:

calculateOutputDataTypes

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

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:

dataTypes - The data types of the inputs

Returns:

The data types of the outputs