Pooling3D.Pooling3DType
DynamicCustomOp.DynamicCustomOpsBuilder
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
Constructor and Description |
---|
MaxPooling3D(INDArray arrayInput,
INDArray arrayOutput,
Pooling3DConfig config) |
MaxPooling3D(INDArray input,
Pooling3DConfig pooling3DConfig) |
MaxPooling3D(SameDiff sameDiff,
SDVariable input,
Pooling3DConfig 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.
|
String |
getPoolingPrefix() |
void |
initFromOnnx(Onnx.NodeProto node,
SameDiff initWith,
Map<String,Onnx.AttributeProto> attributesForNode,
Onnx.GraphProto graph)
Iniitialize the function from the given
Onnx.NodeProto |
boolean |
isConfigProperties()
Returns true if the fields for this class should be looked up from a configuration class.
|
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
|
addArgs, doDiff, iArgs, initFromTensorFlow, onnxName
addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, dArgs, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNull
arg, arg, argNames, args, attributeAdaptersForFunction, diff, dup, equals, getNumOutputs, getValue, hashCode, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
public MaxPooling3D(SameDiff sameDiff, SDVariable input, Pooling3DConfig config)
public MaxPooling3D(INDArray arrayInput, INDArray arrayOutput, Pooling3DConfig config)
public MaxPooling3D(INDArray input, Pooling3DConfig pooling3DConfig)
public boolean isConfigProperties()
DifferentialFunction
isConfigProperties
in class Pooling3D
public String configFieldName()
DifferentialFunction
DifferentialFunction.isConfigProperties()
to facilitate mapping fields for model import.configFieldName
in class Pooling3D
public Map<String,Object> propertiesForFunction()
DifferentialFunction
propertiesForFunction
in class Pooling3D
public String getPoolingPrefix()
getPoolingPrefix
in class Pooling3D
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public void initFromOnnx(Onnx.NodeProto node, SameDiff initWith, Map<String,Onnx.AttributeProto> attributesForNode, Onnx.GraphProto graph)
DifferentialFunction
Onnx.NodeProto
initFromOnnx
in class DynamicCustomOp
public String tensorflowName()
DifferentialFunction
tensorflowName
in class Pooling3D
public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes)
DifferentialFunction
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.calculateOutputDataTypes
in class Pooling3D
inputDataTypes
- The data types of the inputsCopyright © 2021. All rights reserved.