public class MaxPoolWithArgmax extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder| Modifier and Type | Field and Description |
|---|---|
protected Pooling2DConfig |
config |
protected DataType |
outputType |
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArgumentsdimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue| Constructor and Description |
|---|
MaxPoolWithArgmax() |
MaxPoolWithArgmax(@NonNull INDArray input,
INDArray output,
INDArray outArgMax,
@NonNull Pooling2DConfig config) |
MaxPoolWithArgmax(@NonNull INDArray input,
@NonNull Pooling2DConfig config) |
MaxPoolWithArgmax(SameDiff sameDiff,
SDVariable input,
Pooling2DConfig config) |
| Modifier and Type | Method and Description |
|---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> inputDataTypes)
Calculate the data types for the output arrays.
|
String |
configFieldName()
Returns the name of the field to be used for looking up field names.
|
List<SDVariable> |
doDiff(List<SDVariable> f1)
The actual implementation for automatic differentiation.
|
String |
getPoolingPrefix() |
void |
initFromTensorFlow(NodeDef nodeDef,
SameDiff initWith,
Map<String,AttrValue> attributesForNode,
GraphDef graph)
Initialize the function from the given
NodeDef |
boolean |
isConfigProperties()
Returns true if the fields for this class should be looked up from a configuration class.
|
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
|
addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, dArgs, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, initFromOnnx, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNullarg, arg, argNames, args, attributeAdaptersForFunction, diff, dup, equals, getNumOutputs, getValue, hashCode, larg, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNamesclone, finalize, getClass, notify, notifyAll, wait, wait, waitisInplaceCallprotected Pooling2DConfig config
protected DataType outputType
public MaxPoolWithArgmax()
public MaxPoolWithArgmax(SameDiff sameDiff, SDVariable input, Pooling2DConfig config)
public MaxPoolWithArgmax(@NonNull
@NonNull INDArray input,
@NonNull
@NonNull Pooling2DConfig config)
public MaxPoolWithArgmax(@NonNull
@NonNull INDArray input,
INDArray output,
INDArray outArgMax,
@NonNull
@NonNull Pooling2DConfig config)
public boolean isConfigProperties()
DifferentialFunctionisConfigProperties in class DifferentialFunctionpublic String configFieldName()
DifferentialFunctionDifferentialFunction.isConfigProperties()
to facilitate mapping fields for model import.configFieldName in class DifferentialFunctionpublic Map<String,Object> propertiesForFunction()
DifferentialFunctionpropertiesForFunction in class DifferentialFunctionpublic String getPoolingPrefix()
public List<SDVariable> doDiff(List<SDVariable> f1)
DifferentialFunctiondoDiff in class DynamicCustomOppublic void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunctionNodeDefinitFromTensorFlow in class DynamicCustomOppublic Map<String,Map<String,PropertyMapping>> mappingsForFunction()
DifferentialFunctionmappingsForFunction in class DifferentialFunctionpublic String opName()
DynamicCustomOpopName in interface CustomOpopName in class DynamicCustomOppublic String onnxName()
DifferentialFunctiononnxName in class DynamicCustomOppublic String tensorflowName()
DifferentialFunctiontensorflowName in class DynamicCustomOppublic List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes)
DifferentialFunctionDifferentialFunction.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.calculateOutputDataTypes in class DifferentialFunctioninputDataTypes - The data types of the inputsCopyright © 2021. All rights reserved.