public class TensorArrayConcat extends BaseTensorOp
DynamicCustomOp.DynamicCustomOpsBuilderaxis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArgumentsdimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue| Constructor and Description |
|---|
TensorArrayConcat() |
TensorArrayConcat(SameDiff sameDiff,
SDVariable[] args) |
TensorArrayConcat(String name,
SameDiff sameDiff,
SDVariable[] args) |
| Modifier and Type | Method and Description |
|---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> inputDataType)
Calculate the data types for the output arrays.
|
void |
initFromOnnx(Onnx.NodeProto node,
SameDiff initWith,
Map<String,Onnx.AttributeProto> attributesForNode,
Onnx.GraphProto graph)
Iniitialize the function from the given
Onnx.NodeProto |
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
This method returns op opName as string
|
Op.Type |
opType()
The type of the op
|
String[] |
tensorflowNames()
The opName of this function tensorflow
|
String |
toString() |
calculateOutputShape, doDiff, getNumOutputs, initFromTensorFlowaddBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, clearArrays, dArgs, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, tensorflowName, wrapFilterNull, wrapOrNull, wrapOrNullarg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, getValue, hashCode, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueForclone, finalize, getClass, notify, notifyAll, wait, wait, waitisInplaceCallpublic TensorArrayConcat(String name, SameDiff sameDiff, SDVariable[] args)
public TensorArrayConcat(SameDiff sameDiff, SDVariable[] args)
public TensorArrayConcat()
public String onnxName()
DifferentialFunctiononnxName in class BaseTensorOppublic String[] tensorflowNames()
DifferentialFunctiontensorflowNames in class DifferentialFunctionpublic String toString()
toString in class BaseTensorOppublic String opName()
DynamicCustomOpopName in interface CustomOpopName in class DynamicCustomOppublic void initFromOnnx(Onnx.NodeProto node, SameDiff initWith, Map<String,Onnx.AttributeProto> attributesForNode, Onnx.GraphProto graph)
DifferentialFunctionOnnx.NodeProtoinitFromOnnx in class DynamicCustomOppublic Op.Type opType()
DifferentialFunctionopType in class BaseTensorOppublic List<DataType> calculateOutputDataTypes(List<DataType> inputDataType)
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 DifferentialFunctioninputDataType - The data types of the inputsCopyright © 2021. All rights reserved.