public class CompareAndReplace extends BaseTransformSameOp
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexIddimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue| Constructor and Description |
|---|
CompareAndReplace() |
CompareAndReplace(INDArray x,
INDArray y,
Condition condition)
With this constructor, op will check each X element against given Condition, and if condition met, element Z will be set to Y value, and X otherwise
PLEASE NOTE: X will be modified inplace.
|
CompareAndReplace(INDArray x,
INDArray y,
INDArray z,
Condition condition)
With this constructor, op will check each X element against given Condition, and if condition met, element Z will be set to Y value, and X otherwise
Pseudocode:
z[i] = condition(x[i]) ? y[i] : x[i];
|
CompareAndReplace(SameDiff sameDiff,
SDVariable to,
SDVariable from,
Condition condition) |
| 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> grad)
The actual implementation for automatic differentiation.
|
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
The name of the op
|
int |
opNum()
The number of the op (mainly for old legacy XYZ ops
like
Op) |
Map<String,Object> |
propertiesForFunction()
Returns the properties for a given function
|
String |
tensorflowName()
The opName of this function tensorflow
|
calculateOutputShape, calculateOutputShape, getOpType, opType, resultType, resultType, validateDataTypeszclearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, initFromOnnx, initFromTensorFlow, outputVariables, setX, setY, setZ, toCustomOp, toString, x, yarg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNamesclone, finalize, getClass, notify, notifyAll, wait, wait, waitclearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, zpublic CompareAndReplace(SameDiff sameDiff, SDVariable to, SDVariable from, Condition condition)
public CompareAndReplace()
public CompareAndReplace(INDArray x, INDArray y, Condition condition)
x - y - condition - public CompareAndReplace(INDArray x, INDArray y, INDArray z, Condition condition)
x - y - z - condition - public Map<String,Object> propertiesForFunction()
DifferentialFunctionpropertiesForFunction in class DifferentialFunctionpublic int opNum()
DifferentialFunctionOp)opNum in interface OpopNum in class DifferentialFunctionpublic String opName()
DifferentialFunctionopName in interface OpopName in class DifferentialFunctionpublic String onnxName()
DifferentialFunctionpublic String tensorflowName()
DifferentialFunctiontensorflowName in class BaseOppublic List<SDVariable> doDiff(List<SDVariable> grad)
DifferentialFunctiondoDiff in class DifferentialFunctionpublic List<DataType> calculateOutputDataTypes(List<DataType> dataTypes)
DifferentialFunctionDifferentialFunction.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 BaseTransformSameOpdataTypes - The data types of the inputsCopyright © 2021. All rights reserved.