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

Strided Slice function

Author:

Adam Gibson

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

inplaceCall, outputVariables

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

dimensions, extraArgs, inPlace, sameDiff, scalarValue

Constructor Summary

Constructors

Constructor and Description
StridedSlice()
StridedSlice(SameDiff sameDiff, SDVariable in, int[] begin, int[] end, int[] strides)
StridedSlice(SameDiff sameDiff, SDVariable in, int[] begin, int[] end, int[] strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)

Method Summary

Modifier and Type	Method and Description
void	assertValidForExecution() Asserts a valid state for execution, otherwise throws an ND4JIllegalStateException
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
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.DynamicCustomOp

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

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

arg, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, f, getValue, hashCode, hasPlaceHolderInputs, isConfigProperties, larg, onnxNames, 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.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,
                    @NonNull
                    int[] begin,
                    @NonNull
                    int[] end,
                    @NonNull
                    int[] 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 DifferentialFunction

Returns:

propertiesForFunction

public Map<String,Object> propertiesForFunction()

Description copied from class: DifferentialFunction

Returns the properties for a given function

Overrides:

propertiesForFunction in class DifferentialFunction

Returns:

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: