public class TensorArray extends BaseTensorOp
DynamicCustomOp.DynamicCustomOpsBuilder
Modifier and Type | Field and Description |
---|---|
protected DataType |
tensorArrayDataType |
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
TensorArray() |
TensorArray(DataType dataType) |
TensorArray(SameDiff sameDiff,
DataType dataType) |
TensorArray(String name,
SameDiff sameDiff,
DataType dataType) |
TensorArray(TensorArray ta) |
TensorArray(TensorArray ta,
SDVariable[] inputs) |
calculateOutputShape, doDiff, onnxName
addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, clearArrays, dArgs, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, initFromOnnx, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, 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, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
protected DataType tensorArrayDataType
public TensorArray(TensorArray ta)
public TensorArray(TensorArray ta, SDVariable[] inputs)
public TensorArray()
public TensorArray(DataType dataType)
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DynamicCustomOp
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunction
NodeDef
initFromTensorFlow
in class BaseTensorOp
public String toString()
toString
in class BaseTensorOp
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public Op.Type opType()
DifferentialFunction
opType
in class BaseTensorOp
public SameDiff getSameDiff()
public SDVariable read(int index)
public SDVariable read(SDVariable index)
public SDVariable gather(SDVariable flow, int... indices)
public SDVariable gather(SDVariable flow, SDVariable indices)
public SDVariable stack(SDVariable flow)
public SDVariable concat(SDVariable flow)
public SDVariable write(SDVariable flow, int index, SDVariable value)
public SDVariable write(SDVariable flow, SDVariable index, SDVariable value)
public SDVariable scatter(SDVariable flow, SDVariable value, int... indices)
public SDVariable scatter(SDVariable flow, SDVariable value, SDVariable indices)
public SDVariable unstack(SDVariable flow, SDVariable value)
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 inputspublic int getNumOutputs()
getNumOutputs
in class BaseTensorOp
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