public class LocalResponseNormalization extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder, DynamicCustomOp.SameDiffBuilder
Modifier and Type | Field and Description |
---|---|
protected LocalResponseNormalizationConfig |
config |
inplaceCall, outputVariables
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
LocalResponseNormalization(SameDiff sameDiff,
SDVariable[] inputFunctions,
INDArray[] inputs,
INDArray[] outputs,
boolean inPlace,
LocalResponseNormalizationConfig config) |
Modifier and Type | Method and Description |
---|---|
List<SDVariable> |
doDiff(List<SDVariable> f1)
The actual implementation for automatic differentiation.
|
void |
initFromOnnx(OnnxProto3.NodeProto node,
SameDiff initWith,
Map<String,OnnxProto3.AttributeProto> attributesForNode,
OnnxProto3.GraphProto graph)
Iniitialize the function from the given
OnnxProto3.NodeProto |
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 |
onnxName()
The opName of this function in onnx
|
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
|
addIArgument, addInputArgument, addOutputArgument, addTArgument, asProperties, assertValidForExecution, builder, calculateOutputShape, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, inputArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, populateInputsAndOutputsFromSameDiff, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, sameDiffBuilder, setInputArgument, setOutputArgument, tArgs, toString, updateInputsFromSameDiff
arg, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, f, getValue, hashCode, hasPlaceHolderInputs, isConfigProperties, larg, onnxNames, rarg, resolvePropertiesFromSameDiffBeforeExecution, setInstanceId, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
protected LocalResponseNormalizationConfig config
public LocalResponseNormalization(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputs, INDArray[] outputs, boolean inPlace, LocalResponseNormalizationConfig config)
public Map<String,Object> propertiesForFunction()
DifferentialFunction
propertiesForFunction
in class DifferentialFunction
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunction
NodeDef
initFromTensorFlow
in class DynamicCustomOp
public void initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
DifferentialFunction
OnnxProto3.NodeProto
initFromOnnx
in class DynamicCustomOp
public Map<String,Map<String,PropertyMapping>> mappingsForFunction()
DifferentialFunction
mappingsForFunction
in class DifferentialFunction
public List<SDVariable> doDiff(List<SDVariable> f1)
DifferentialFunction
doDiff
in class DynamicCustomOp
public String onnxName()
DifferentialFunction
onnxName
in class DynamicCustomOp
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DynamicCustomOp
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