public abstract class BaseReduceFloatOp extends BaseReduceOp implements ReduceFloatOp
isComplex, isEmptyReduce, keepDims
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, extraArgs, inPlace, 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, setDimensions
clearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, 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, isComplexAccumulation, isKeepDims, noOp, setDimensions
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, opName, opNum, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z
public 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()
DifferentialFunction
opType
in class DifferentialFunction
public DataType resultType()
ReduceOp
resultType
in interface ReduceOp
public DataType resultType(OpContext oc)
resultType
in interface ReduceOp
public boolean validateDataTypes(OpContext oc)
validateDataTypes
in interface ReduceOp
public List<LongShapeDescriptor> calculateOutputShape()
DifferentialFunction
calculateOutputShape
in class BaseReduceOp
public List<LongShapeDescriptor> calculateOutputShape(OpContext oc)
calculateOutputShape
in class DifferentialFunction
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.