DynamicCustomOp.DynamicCustomOpsBuilder
Modifier and Type | Field and Description |
---|---|
static double |
DEFAULT_LABEL_SMOOTHING |
lossReduce
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
SoftmaxCrossEntropyLoss(INDArray labels,
INDArray predictions,
INDArray weights,
LossReduce lossReduce,
double labelSmoothing) |
SoftmaxCrossEntropyLoss(SameDiff sameDiff,
LossReduce lossReduce,
SDVariable logits,
SDVariable weights,
SDVariable labels) |
SoftmaxCrossEntropyLoss(SameDiff sameDiff,
LossReduce lossReduce,
SDVariable logits,
SDVariable weights,
SDVariable labels,
double labelSmoothing) |
SoftmaxCrossEntropyLoss(SameDiff sameDiff,
SDVariable labels,
SDVariable logits,
SDVariable weights,
LossReduce lossReduce,
double labelSmoothing) |
Modifier and Type | Method and Description |
---|---|
void |
addArgs() |
List<SDVariable> |
doDiff(List<SDVariable> grad)
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 |
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
This method returns op opName as string
|
String |
tensorflowName()
The opName of this function tensorflow
|
calculateOutputDataTypes, getWeights, getWeights
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, 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, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
public static final double DEFAULT_LABEL_SMOOTHING
public SoftmaxCrossEntropyLoss(SameDiff sameDiff, SDVariable labels, SDVariable logits, SDVariable weights, LossReduce lossReduce, double labelSmoothing)
public SoftmaxCrossEntropyLoss(SameDiff sameDiff, LossReduce lossReduce, SDVariable logits, SDVariable weights, SDVariable labels, double labelSmoothing)
public SoftmaxCrossEntropyLoss(SameDiff sameDiff, LossReduce lossReduce, SDVariable logits, SDVariable weights, SDVariable labels)
public SoftmaxCrossEntropyLoss(INDArray labels, INDArray predictions, INDArray weights, LossReduce lossReduce, double labelSmoothing)
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunction
NodeDef
initFromTensorFlow
in class DynamicCustomOp
public String opName()
DynamicCustomOp
public String onnxName()
DifferentialFunction
onnxName
in class DynamicCustomOp
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DynamicCustomOp
public List<SDVariable> doDiff(List<SDVariable> grad)
DifferentialFunction
doDiff
in class DynamicCustomOp
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