public class DepthToSpace extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
Constructor and Description |
---|
DepthToSpace() |
DepthToSpace(INDArray in,
INDArray out,
int blockSize,
DataFormat dataFormat) |
DepthToSpace(INDArray in,
int blockSize,
DataFormat dataFormat) |
DepthToSpace(SameDiff sameDiff,
SDVariable[] args,
int blockSize,
DataFormat dataFormat) |
DepthToSpace(SameDiff sameDiff,
SDVariable args,
int blockSize,
DataFormat dataFormat) |
Modifier and Type | Method and Description |
---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> dataTypes)
Calculate the data types for the output arrays.
|
List<SDVariable> |
doDiff(List<SDVariable> i_v)
The actual implementation for automatic differentiation.
|
void |
initFromTensorFlow(NodeDef nodeDef,
SameDiff initWith,
Map<String,AttrValue> attributesForNode,
GraphDef graph)
Initialize the function from the given
NodeDef |
Map<String,Map<String,PropertyMapping>> |
mappingsForFunction()
Returns the mappings for a given function (
for tensorflow and onnx import mapping properties
of this function).
|
String |
opName()
This method returns op opName as string
|
String |
tensorflowName()
The opName of this function tensorflow
|
String[] |
tensorflowNames()
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, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNull
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, getNumOutputs, getValue, hashCode, isConfigProperties, larg, onnxNames, outputs, outputVariable, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
public DepthToSpace()
public DepthToSpace(SameDiff sameDiff, SDVariable args, int blockSize, DataFormat dataFormat)
public DepthToSpace(SameDiff sameDiff, SDVariable[] args, int blockSize, DataFormat dataFormat)
public DepthToSpace(INDArray in, INDArray out, int blockSize, DataFormat dataFormat)
public DepthToSpace(INDArray in, int blockSize, DataFormat dataFormat)
public List<SDVariable> doDiff(List<SDVariable> i_v)
DifferentialFunction
doDiff
in class DynamicCustomOp
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunction
NodeDef
initFromTensorFlow
in class DynamicCustomOp
public Map<String,Map<String,PropertyMapping>> mappingsForFunction()
DifferentialFunction
mappingsForFunction
in class DifferentialFunction
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public String[] tensorflowNames()
DifferentialFunction
tensorflowNames
in class DifferentialFunction
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DynamicCustomOp
public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes)
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
dataTypes
- The data types of the inputsCopyright © 2021. All rights reserved.