public abstract class BaseTransformFloatOp extends BaseTransformOp implements TransformFloatOp
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
Constructor and Description |
---|
BaseTransformFloatOp() |
BaseTransformFloatOp(INDArray x) |
BaseTransformFloatOp(INDArray x,
INDArray z) |
BaseTransformFloatOp(SameDiff sameDiff,
SDVariable i_v,
boolean inPlace) |
BaseTransformFloatOp(SameDiff sameDiff,
SDVariable i_v,
long[] shape,
boolean inPlace,
Object[] extraArgs) |
BaseTransformFloatOp(SameDiff sameDiff,
SDVariable i_v,
Object[] extraArgs) |
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,
boolean experimentalMode) |
z
clearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, initFromOnnx, initFromTensorFlow, onnxName, outputVariables, setX, setY, setZ, tensorflowName, toCustomOp, toString, x, y
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
public BaseTransformFloatOp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
public BaseTransformFloatOp(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
public BaseTransformFloatOp(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
public BaseTransformFloatOp()
public BaseTransformFloatOp(INDArray x)
public Op.Type getOpType()
getOpType
in interface TransformOp
public Op.Type opType()
DifferentialFunction
opType
in class DifferentialFunction
public DataType resultType()
TransformOp
resultType
in interface TransformOp
public DataType resultType(OpContext oc)
resultType
in interface TransformOp
public boolean validateDataTypes(OpContext oc, boolean experimentalMode)
validateDataTypes
in interface TransformOp
public List<LongShapeDescriptor> calculateOutputShape()
DifferentialFunction
calculateOutputShape
in class BaseTransformOp
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 © 2021. All rights reserved.