public class TensorArrayRead extends BaseTensorOp
DynamicCustomOp.DynamicCustomOpsBuilder
Modifier and Type | Field and Description |
---|---|
protected DataType |
importDataType |
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
TensorArrayRead() |
TensorArrayRead(SameDiff sameDiff,
SDVariable[] args) |
TensorArrayRead(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 |
void |
initFromTensorFlow(NodeDef nodeDef,
SameDiff initWith,
Map<String,AttrValue> attributesForNode,
GraphDef graph)
Initialize the function from the given
NodeDef |
String |
opName()
This method returns op opName as string
|
String[] |
tensorflowNames()
The opName of this function tensorflow
|
calculateOutputShape, doDiff, getNumOutputs, onnxName, opType, toString
addBArgument, 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, wrapOrNull
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, getValue, hashCode, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
protected DataType importDataType
public TensorArrayRead(String name, SameDiff sameDiff, SDVariable[] args)
public TensorArrayRead(SameDiff sameDiff, SDVariable[] args)
public TensorArrayRead()
public String[] tensorflowNames()
DifferentialFunction
tensorflowNames
in class DifferentialFunction
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 void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunction
NodeDef
initFromTensorFlow
in class BaseTensorOp
public List<DataType> calculateOutputDataTypes(List<DataType> inputDataType)
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 DifferentialFunction
inputDataType
- The data types of the inputsCopyright © 2020. All rights reserved.