public abstract class BaseRandomOp extends BaseOp implements RandomOp
Modifier and Type | Field and Description |
---|---|
protected DataType |
dataType |
protected long[] |
shape |
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
BaseRandomOp(INDArray x,
INDArray y,
INDArray z) |
BaseRandomOp(SameDiff sd,
long[] shape) |
BaseRandomOp(SameDiff sameDiff,
SDVariable i_v) |
Modifier and Type | Method and Description |
---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> inputDataTypes)
Calculate the data types for the output arrays.
|
List<LongShapeDescriptor> |
calculateOutputShape()
Calculate the output shape for this op
|
List<LongShapeDescriptor> |
calculateOutputShape(OpContext opContext) |
boolean |
isInPlace() |
boolean |
isTripleArgRngOp() |
Op.Type |
opType()
The type of the op
|
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
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, opName, opNum, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z
protected long[] shape
protected DataType dataType
public BaseRandomOp(SameDiff sameDiff, SDVariable i_v)
public BaseRandomOp(SameDiff sd, long[] shape)
public Op.Type opType()
DifferentialFunction
opType
in class DifferentialFunction
public List<LongShapeDescriptor> calculateOutputShape()
DifferentialFunction
calculateOutputShape
in class DifferentialFunction
public List<LongShapeDescriptor> calculateOutputShape(OpContext opContext)
calculateOutputShape
in class DifferentialFunction
public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes)
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
inputDataTypes
- The data types of the inputspublic boolean isInPlace()
public boolean isTripleArgRngOp()
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