public abstract class BaseIndexAccumulation extends BaseOp implements IndexAccumulation
Modifier and Type | Field and Description |
---|---|
protected boolean |
keepDims |
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
BaseIndexAccumulation() |
BaseIndexAccumulation(INDArray x,
boolean keepDims,
int[] dimensions) |
BaseIndexAccumulation(INDArray x,
INDArray z,
int[] dimensions) |
BaseIndexAccumulation(INDArray x,
int[] dimensions) |
BaseIndexAccumulation(SameDiff sameDiff,
SDVariable i_v,
boolean keepDims,
int[] dimensions) |
BaseIndexAccumulation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
boolean keepDims,
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 |
opType()
The type of the op
|
boolean |
validateDataTypes() |
clearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, initFromOnnx, initFromTensorFlow, onnxName, outputVariables, setX, setY, setZ, tensorflowName, toCustomOp, toString, x, y, z
arg, 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, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
dimensions, getFinalResult, isKeepDims
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, opName, opNum, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z
public BaseIndexAccumulation(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
public BaseIndexAccumulation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, boolean keepDims, int[] dimensions)
public BaseIndexAccumulation()
public BaseIndexAccumulation(INDArray x, int[] dimensions)
public BaseIndexAccumulation(INDArray x, boolean keepDims, int[] dimensions)
public List<LongShapeDescriptor> calculateOutputShape()
DifferentialFunction
calculateOutputShape
in class DifferentialFunction
public List<LongShapeDescriptor> calculateOutputShape(OpContext oc)
calculateOutputShape
in class DifferentialFunction
public Op.Type opType()
DifferentialFunction
opType
in class DifferentialFunction
public boolean validateDataTypes()
validateDataTypes
in interface IndexAccumulation
public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes)
DifferentialFunction
DifferentialFunction.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 DifferentialFunction
dataTypes
- The data types of the inputsCopyright © 2020. All rights reserved.