public abstract class BaseReduceBoolOp extends BaseReduceOp implements ReduceBoolOp
isComplex, isEmptyReduce, keepDims
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
Modifier | Constructor and Description |
---|---|
protected |
BaseReduceBoolOp() |
|
BaseReduceBoolOp(INDArray x,
INDArray z,
boolean keepDims,
int[] dimensions) |
|
BaseReduceBoolOp(INDArray x,
INDArray z,
int... dimensions) |
|
BaseReduceBoolOp(INDArray x,
int... dimensions) |
protected |
BaseReduceBoolOp(SameDiff sameDiff,
SDVariable input,
int... dimensions) |
protected |
BaseReduceBoolOp(SameDiff sameDiff,
SDVariable input,
int[] dimensions,
boolean keepDims) |
|
BaseReduceBoolOp(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) |
abstract boolean |
emptyValue() |
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 BaseReduceBoolOp(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
protected BaseReduceBoolOp(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims)
protected BaseReduceBoolOp(SameDiff sameDiff, SDVariable input, int... dimensions)
public BaseReduceBoolOp(INDArray x, INDArray z, boolean keepDims, int[] dimensions)
public BaseReduceBoolOp(INDArray x, int... dimensions)
protected BaseReduceBoolOp()
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 inputspublic abstract boolean emptyValue()
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