public class And extends BaseTransformOp
Modifier and Type | Field and Description |
---|---|
protected double |
comparable |
extraArgs, extraArgz, n, numProcessed, passThrough, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
And() |
And(INDArray x,
INDArray y) |
And(INDArray x,
INDArray y,
INDArray z) |
And(INDArray x,
INDArray y,
INDArray z,
long n) |
And(INDArray x,
INDArray y,
INDArray z,
Number comparable) |
And(INDArray x,
INDArray y,
INDArray z,
Number comparable,
long n) |
And(INDArray x,
INDArray y,
long n) |
And(INDArray x,
INDArray y,
Number comparable) |
And(SameDiff sameDiff,
SDVariable i_v,
boolean inPlace) |
And(SameDiff sameDiff,
SDVariable i_v,
boolean inPlace,
double comparable) |
And(SameDiff sameDiff,
SDVariable i_v,
int[] shape,
boolean inPlace,
Object[] extraArgs) |
And(SameDiff sameDiff,
SDVariable i_v,
int[] shape,
boolean inPlace,
Object[] extraArgs,
double comparable) |
And(SameDiff sameDiff,
SDVariable i_v,
Object[] extraArgs) |
And(SameDiff sameDiff,
SDVariable i_v,
Object[] extraArgs,
double comparable) |
And(SameDiff sameDiff,
SDVariable ix,
SDVariable iy) |
Modifier and Type | Method and Description |
---|---|
List<SDVariable> |
doDiff(List<SDVariable> f1)
The actual implementation for automatic differentiation.
|
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
The name of the op
|
int |
opNum()
The number of the op (mainly for old legacy XYZ ops
like
Op ) |
String |
tensorflowName()
The opName of this function tensorflow
|
calculateOutputShape, opType, z
equals, exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, getOpType, hashCode, init, initFromOnnx, initFromTensorFlow, isExecSpecial, isPassThrough, n, numProcessed, outputVariables, setN, setX, setY, setZ, toCustomOp, toString, x, y
arg, args, asProperties, attributeAdaptersForFunction, configFieldName, diff, dup, f, getValue, hasPlaceHolderInputs, isConfigProperties, larg, mappingsForFunction, onnxNames, outputVariables, propertiesForFunction, rarg, resolvePropertiesFromSameDiffBeforeExecution, setInstanceId, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
exec, exec, extraArgs, extraArgsBuff, extraArgsDataBuff, init, isExecSpecial, isPassThrough, n, numProcessed, setExtraArgs, setN, setX, setY, setZ, toCustomOp, x, y
public And(SameDiff sameDiff, SDVariable ix, SDVariable iy)
public And(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
public And(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
public And(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
public And(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double comparable)
public And(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double comparable)
public And(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double comparable)
public And()
public int opNum()
DifferentialFunction
Op
)opNum
in interface Op
opNum
in class DifferentialFunction
public String opName()
DifferentialFunction
opName
in interface Op
opName
in class DifferentialFunction
public String onnxName()
DifferentialFunction
onnxName
in class DifferentialFunction
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DifferentialFunction
public List<SDVariable> doDiff(List<SDVariable> f1)
DifferentialFunction
doDiff
in class DifferentialFunction
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