Class SwishDerivative
- java.lang.Object
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- org.nd4j.autodiff.functions.DifferentialFunction
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- org.nd4j.linalg.api.ops.BaseOp
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- org.nd4j.linalg.api.ops.BaseTransformOp
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- org.nd4j.linalg.api.ops.BaseTransformStrictOp
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- org.nd4j.linalg.api.ops.impl.transforms.strict.SwishDerivative
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- All Implemented Interfaces:
Op,TransformOp,TransformStrictOp
public class SwishDerivative extends BaseTransformStrictOp
Swish derivative- Author:
- Adam Gibson
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Field Summary
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Fields inherited from class org.nd4j.linalg.api.ops.BaseOp
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
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Fields inherited from class org.nd4j.autodiff.functions.DifferentialFunction
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
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Constructor Summary
Constructors Constructor Description SwishDerivative()SwishDerivative(SameDiff sameDiff, SDVariable i_v)SwishDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)SwishDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)SwishDerivative(INDArray x)SwishDerivative(INDArray x, INDArray z)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description List<SDVariable>doDiff(List<SDVariable> f1)The actual implementation for automatic differentiation.StringonnxName()The opName of this function in onnxStringopName()The name of the opintopNum()The number of the op (mainly for old legacy XYZ ops likeOp)StringtensorflowName()The opName of this function tensorflow-
Methods inherited from class org.nd4j.linalg.api.ops.BaseTransformStrictOp
calculateOutputDataTypes, calculateOutputShape, calculateOutputShape, getOpType, opType, resultType, resultType, validateDataTypes
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Methods inherited from class org.nd4j.linalg.api.ops.BaseTransformOp
z
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Methods inherited from class org.nd4j.linalg.api.ops.BaseOp
clearArrays, computeVariables, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, initFromOnnx, initFromTensorFlow, outputVariables, setX, setY, setZ, toCustomOp, toString, x, y
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Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, configureWithSameDiff, diff, dup, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNames
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Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
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Methods inherited from interface org.nd4j.linalg.api.ops.Op
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z
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Constructor Detail
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SwishDerivative
public SwishDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
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SwishDerivative
public SwishDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
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SwishDerivative
public SwishDerivative(SameDiff sameDiff, SDVariable i_v)
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SwishDerivative
public SwishDerivative()
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SwishDerivative
public SwishDerivative(INDArray x)
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Method Detail
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opNum
public int opNum()
Description copied from class:DifferentialFunctionThe number of the op (mainly for old legacy XYZ ops likeOp)- Specified by:
opNumin interfaceOp- Overrides:
opNumin classDifferentialFunction- Returns:
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opName
public String opName()
Description copied from class:DifferentialFunctionThe name of the op- Specified by:
opNamein interfaceOp- Overrides:
opNamein classDifferentialFunction- Returns:
- the opName of this operation
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onnxName
public String onnxName()
Description copied from class:DifferentialFunctionThe opName of this function in onnx
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tensorflowName
public String tensorflowName()
Description copied from class:DifferentialFunctionThe opName of this function tensorflow- Overrides:
tensorflowNamein classBaseOp- Returns:
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doDiff
public List<SDVariable> doDiff(List<SDVariable> f1)
Description copied from class:DifferentialFunctionThe actual implementation for automatic differentiation.- Specified by:
doDiffin classDifferentialFunction- Returns:
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