public abstract class BaseTransformAnyOp extends BaseTransformOp implements TransformSameOp
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexIddimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue| Constructor and Description |
|---|
BaseTransformAnyOp() |
BaseTransformAnyOp(INDArray x) |
BaseTransformAnyOp(INDArray x,
INDArray z) |
BaseTransformAnyOp(INDArray x,
INDArray y,
INDArray z) |
BaseTransformAnyOp(SameDiff sameDiff) |
BaseTransformAnyOp(SameDiff sameDiff,
SDVariable i_v,
boolean inPlace) |
BaseTransformAnyOp(SameDiff sameDiff,
SDVariable i_v,
long[] shape,
boolean inPlace,
Object[] extraArgs) |
BaseTransformAnyOp(SameDiff sameDiff,
SDVariable i_v,
Object[] extraArgs) |
BaseTransformAnyOp(SameDiff sameDiff,
SDVariable i_v1,
SDVariable i_v2) |
BaseTransformAnyOp(SameDiff sameDiff,
SDVariable i_v1,
SDVariable i_v2,
boolean inPlace) |
BaseTransformAnyOp(SameDiff sameDiff,
SDVariable i_v1,
SDVariable i_v2,
Object[] extraArgs) |
| Modifier and Type | Method and Description |
|---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> dataTypes)
Calculate the data types for the output arrays.
|
List<LongShapeDescriptor> |
calculateOutputShape()
Calculate the output shape for this op
|
Op.Type |
getOpType() |
Op.Type |
opType()
The type of the op
|
DataType |
resultType()
This method returns datatype for result array wrt given inputs
|
DataType |
resultType(OpContext oc) |
boolean |
validateDataTypes(OpContext oc,
boolean experimentalMode) |
zclearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, initFromOnnx, initFromTensorFlow, onnxName, outputVariables, setX, setY, setZ, tensorflowName, toCustomOp, toString, x, yarg, arg, argNames, args, attributeAdaptersForFunction, calculateOutputShape, configFieldName, diff, doDiff, dup, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, opName, opNum, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNamesclone, finalize, getClass, notify, notifyAll, wait, wait, waitclearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, opName, opNum, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, zpublic BaseTransformAnyOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
public BaseTransformAnyOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
public BaseTransformAnyOp(SameDiff sameDiff)
public BaseTransformAnyOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
public BaseTransformAnyOp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
public BaseTransformAnyOp(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
public BaseTransformAnyOp(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
public BaseTransformAnyOp()
public BaseTransformAnyOp(INDArray x)
public Op.Type getOpType()
getOpType in interface TransformOppublic Op.Type opType()
DifferentialFunctionopType in class DifferentialFunctionpublic DataType resultType()
TransformOpresultType in interface TransformOppublic DataType resultType(OpContext oc)
resultType in interface TransformOppublic boolean validateDataTypes(OpContext oc, boolean experimentalMode)
validateDataTypes in interface TransformOppublic List<LongShapeDescriptor> calculateOutputShape()
DifferentialFunctioncalculateOutputShape in class BaseTransformOppublic 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 DifferentialFunctiondataTypes - The data types of the inputsCopyright © 2021. All rights reserved.