public class TanhDerivative extends BaseGradientOp
extraArgs, extraArgz, n, numProcessed, passThrough, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
TanhDerivative() |
TanhDerivative(INDArray x) |
TanhDerivative(INDArray x,
INDArray z) |
TanhDerivative(INDArray x,
INDArray y,
INDArray z) |
TanhDerivative(INDArray x,
INDArray z,
long n) |
TanhDerivative(SameDiff sameDiff,
SDVariable i_v1,
SDVariable i_v2) |
TanhDerivative(SameDiff sameDiff,
SDVariable i_v1,
SDVariable i_v2,
boolean inPlace) |
Modifier and Type | Method and Description |
---|---|
List<SDVariable> |
doDiff(List<SDVariable> i_v)
The actual implementation for automatic differentiation.
|
void |
exec()
Execute the op if its pass through (not needed most of the time)
|
void |
exec(int... dimensions)
Exec along each dimension
|
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
The opName of this operation
|
int |
opNum()
An op number
|
String |
tensorflowName()
The opName of this function tensorflow
|
isExecSpecial, isPassThrough, wrt
calculateOutputShape, opType, z
equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getOpType, hashCode, init, initFromOnnx, initFromTensorFlow, 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
extraArgs, extraArgsBuff, extraArgsDataBuff, init, n, numProcessed, setExtraArgs, setN, setX, setY, setZ, toCustomOp, x, y, z
public TanhDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
public TanhDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
public TanhDerivative()
public TanhDerivative(INDArray x)
public int opNum()
opNum
in interface Op
opNum
in class DifferentialFunction
public String opName()
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 void exec()
Op
public void exec(int... dimensions)
Op
public List<SDVariable> doDiff(List<SDVariable> i_v)
DifferentialFunction
doDiff
in class DifferentialFunction
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