Class LogSoftMaxDerivative
- java.lang.Object
-
- org.nd4j.autodiff.functions.DifferentialFunction
-
- org.nd4j.linalg.api.ops.DynamicCustomOp
-
- org.nd4j.linalg.api.ops.impl.transforms.gradient.LogSoftMaxDerivative
-
- All Implemented Interfaces:
CustomOp
public class LogSoftMaxDerivative extends DynamicCustomOp
-
-
Nested Class Summary
-
Nested classes/interfaces inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder
-
-
Field Summary
-
Fields inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, sArguments, tArguments
-
Fields inherited from class org.nd4j.autodiff.functions.DifferentialFunction
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
-
-
Constructor Summary
Constructors Constructor Description LogSoftMaxDerivative()
LogSoftMaxDerivative(SameDiff sameDiff, SDVariable in, SDVariable gradO)
LogSoftMaxDerivative(SameDiff sameDiff, SDVariable arg, SDVariable wrt, int dimension)
LogSoftMaxDerivative(INDArray in, INDArray gradO, INDArray out)
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description List<DataType>
calculateOutputDataTypes(List<DataType> inTypes)
Calculate the data types for the output arrays.List<SDVariable>
doDiff(List<SDVariable> i_v)
The actual implementation for automatic differentiation.String
onnxName()
The opName of this function in onnxString
opName()
The opName of this operationString
tensorflowName()
The opName of this function tensorflow-
Methods inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addOutputsToOp, addSArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, computeArrays, configureFromArguments, dArgs, generateFake, generateFake, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getSArgument, getTArgument, getValue, iArgs, initFromOnnx, initFromTensorFlow, inputArguments, mappingsForFunction, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numSArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, propertiesForFunction, removeIArgument, removeInputArgument, removeOutputArgument, removeSArgument, removeTArgument, sArgs, setInputArgument, setInputArguments, setOutputArgument, setPropertiesForFunction, setValueFor, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNull
-
Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, configureWithSameDiff, diff, dup, equals, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getNumOutputs, getStringFromProperty, hashCode, isConfigProperties, larg, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, tensorflowNames
-
Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
-
Methods inherited from interface org.nd4j.linalg.api.ops.CustomOp
isInplaceCall
-
-
-
-
Constructor Detail
-
LogSoftMaxDerivative
public LogSoftMaxDerivative(SameDiff sameDiff, SDVariable in, SDVariable gradO)
-
LogSoftMaxDerivative
public LogSoftMaxDerivative()
-
LogSoftMaxDerivative
public LogSoftMaxDerivative(SameDiff sameDiff, SDVariable arg, SDVariable wrt, int dimension)
-
-
Method Detail
-
opName
public String opName()
The opName of this operation- Specified by:
opName
in interfaceCustomOp
- Overrides:
opName
in classDynamicCustomOp
- Returns:
- the opName of this operation
-
onnxName
public String onnxName()
Description copied from class:DifferentialFunction
The opName of this function in onnx- Overrides:
onnxName
in classDynamicCustomOp
- Returns:
-
tensorflowName
public String tensorflowName()
Description copied from class:DifferentialFunction
The opName of this function tensorflow- Overrides:
tensorflowName
in classDynamicCustomOp
- Returns:
-
doDiff
public List<SDVariable> doDiff(List<SDVariable> i_v)
Description copied from class:DifferentialFunction
The actual implementation for automatic differentiation.- Overrides:
doDiff
in classDynamicCustomOp
- Returns:
-
calculateOutputDataTypes
public List<DataType> calculateOutputDataTypes(List<DataType> inTypes)
Description copied from class:DifferentialFunction
Calculate the data types for the output arrays. Though datatypes can also be inferred fromDifferentialFunction.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.- Overrides:
calculateOutputDataTypes
in classDifferentialFunction
- Parameters:
inTypes
- The data types of the inputs- Returns:
- The data types of the outputs
-
-