public abstract class BaseReduceFloatOp extends BaseReduceOp implements ReduceFloatOp
isComplex, isEmptyReduce, keepDimsdimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexIddimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue| Modifier | Constructor and Description |
|---|---|
protected |
BaseReduceFloatOp() |
|
BaseReduceFloatOp(INDArray x,
boolean keepDims,
int... dimensions) |
|
BaseReduceFloatOp(INDArray input,
INDArray output,
boolean keepDims,
int... dimensions) |
|
BaseReduceFloatOp(INDArray x,
INDArray y,
INDArray z,
boolean keepDims,
int... dimensions) |
|
BaseReduceFloatOp(INDArray x,
INDArray y,
INDArray z,
int... dimensions) |
|
BaseReduceFloatOp(INDArray x,
INDArray z,
int... dimensions) |
|
BaseReduceFloatOp(INDArray x,
int... dimensions) |
protected |
BaseReduceFloatOp(SameDiff sameDiff,
SDVariable i_v,
boolean keepDims,
int[] dimensions) |
protected |
BaseReduceFloatOp(SameDiff sameDiff,
SDVariable input,
int... dimensions) |
protected |
BaseReduceFloatOp(SameDiff sameDiff,
SDVariable input,
int[] dimensions,
boolean keepDims) |
protected |
BaseReduceFloatOp(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
int[] dimensions) |
| 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
|
List<LongShapeDescriptor> |
calculateOutputShape(OpContext oc) |
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) |
hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, noOp, setDimensionsclearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, onnxName, outputVariables, setX, setY, setZ, tensorflowName, toCustomOp, toString, x, y, zarg, arg, argNames, args, attributeAdaptersForFunction, 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, waitdimensions, getFinalResult, isComplexAccumulation, isKeepDims, noOp, setDimensionsclearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, opName, opNum, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, zpublic BaseReduceFloatOp(INDArray x, INDArray y, INDArray z, boolean keepDims, int... dimensions)
protected BaseReduceFloatOp(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
protected BaseReduceFloatOp(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
protected BaseReduceFloatOp(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims)
protected BaseReduceFloatOp(SameDiff sameDiff, SDVariable input, int... dimensions)
public BaseReduceFloatOp(INDArray input, INDArray output, boolean keepDims, int... dimensions)
public BaseReduceFloatOp(INDArray x, boolean keepDims, int... dimensions)
public BaseReduceFloatOp(INDArray x, int... dimensions)
protected BaseReduceFloatOp()
public Op.Type opType()
DifferentialFunctionopType in class DifferentialFunctionpublic DataType resultType()
ReduceOpresultType in interface ReduceOppublic DataType resultType(OpContext oc)
resultType in interface ReduceOppublic boolean validateDataTypes(OpContext oc)
validateDataTypes in interface ReduceOppublic List<LongShapeDescriptor> calculateOutputShape()
DifferentialFunctioncalculateOutputShape in class BaseReduceOppublic List<LongShapeDescriptor> calculateOutputShape(OpContext oc)
calculateOutputShape 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 DifferentialFunctiondataTypes - The data types of the inputsCopyright © 2021. All rights reserved.