Class SquaredNorm
- 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.BaseReduceOp
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- org.nd4j.linalg.api.ops.BaseReduceFloatOp
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- org.nd4j.linalg.api.ops.impl.reduce.floating.SquaredNorm
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- All Implemented Interfaces:
Op
,ReduceFloatOp
,ReduceOp
public class SquaredNorm extends BaseReduceFloatOp
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Field Summary
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Fields inherited from class org.nd4j.linalg.api.ops.BaseReduceOp
dimensionVariable, isComplex, isEmptyReduce, keepDims
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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 SquaredNorm()
SquaredNorm(SameDiff sameDiff, SDVariable input, boolean keepDims, int... dimensions)
SquaredNorm(SameDiff sameDiff, SDVariable i_v, boolean keepDims, SDVariable dimensions)
SquaredNorm(SameDiff sameDiff, SDVariable input, int... dimensions)
SquaredNorm(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims)
SquaredNorm(SameDiff sameDiff, SDVariable input, SDVariable dimensions)
SquaredNorm(SameDiff sameDiff, SDVariable input, SDVariable dimensions, boolean keepDims)
SquaredNorm(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
SquaredNorm(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions)
SquaredNorm(INDArray input, boolean keepDims, int... dimensions)
SquaredNorm(INDArray x, int... dimensions)
SquaredNorm(INDArray in, int[] dimensions, boolean keepDims)
SquaredNorm(INDArray input, INDArray output, boolean keepDims, int... dimensions)
SquaredNorm(INDArray x, INDArray z, int... dimensions)
SquaredNorm(INDArray x, INDArray y, INDArray z, boolean keepDims, int... dimensions)
SquaredNorm(INDArray x, INDArray y, INDArray z, int... dimensions)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description List<SDVariable>
doDiff(List<SDVariable> grad)
The actual implementation for automatic differentiation.String
onnxName()
The opName of this function in onnxString
opName()
The name of the opint
opNum()
The number of the op (mainly for old legacy XYZ ops likeOp
)String
tensorflowName()
The opName of this function tensorflow-
Methods inherited from class org.nd4j.linalg.api.ops.BaseReduceFloatOp
calculateOutputDataTypes, calculateOutputShape, calculateOutputShape, getOpType, opType, resultType, resultType, validateDataTypes
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Methods inherited from class org.nd4j.linalg.api.ops.BaseReduceOp
configureWithSameDiff, hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, noOp, setDimensions, setPropertiesForFunction
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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, outputVariables, setX, setY, setZ, toCustomOp, toString, x, y, z
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Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, 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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Methods inherited from interface org.nd4j.linalg.api.ops.ReduceOp
dimensions, getFinalResult, isComplexAccumulation, isKeepDims, noOp, setDimensions
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Constructor Detail
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SquaredNorm
public SquaredNorm(SameDiff sameDiff, SDVariable input, boolean keepDims, int... dimensions)
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SquaredNorm
public SquaredNorm(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
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SquaredNorm
public SquaredNorm(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims)
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SquaredNorm
public SquaredNorm(SameDiff sameDiff, SDVariable input, int... dimensions)
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SquaredNorm
public SquaredNorm(SameDiff sameDiff, SDVariable i_v, boolean keepDims, SDVariable dimensions)
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SquaredNorm
public SquaredNorm(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions)
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SquaredNorm
public SquaredNorm(SameDiff sameDiff, SDVariable input, SDVariable dimensions, boolean keepDims)
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SquaredNorm
public SquaredNorm(SameDiff sameDiff, SDVariable input, SDVariable dimensions)
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SquaredNorm
public SquaredNorm(INDArray input, INDArray output, boolean keepDims, int... dimensions)
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SquaredNorm
public SquaredNorm(INDArray input, boolean keepDims, int... dimensions)
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SquaredNorm
public SquaredNorm()
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SquaredNorm
public SquaredNorm(INDArray x, int... dimensions)
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SquaredNorm
public SquaredNorm(INDArray x, INDArray y, INDArray z, boolean keepDims, int... dimensions)
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SquaredNorm
public SquaredNorm(INDArray in, int[] dimensions, boolean keepDims)
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Method Detail
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opNum
public int opNum()
Description copied from class:DifferentialFunction
The number of the op (mainly for old legacy XYZ ops likeOp
)- Specified by:
opNum
in interfaceOp
- Overrides:
opNum
in classDifferentialFunction
- Returns:
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opName
public String opName()
Description copied from class:DifferentialFunction
The name of the op- Specified by:
opName
in interfaceOp
- Overrides:
opName
in classDifferentialFunction
- Returns:
- the opName of this operation
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onnxName
public String onnxName()
Description copied from class:DifferentialFunction
The opName of this function in onnx
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tensorflowName
public String tensorflowName()
Description copied from class:DifferentialFunction
The opName of this function tensorflow- Overrides:
tensorflowName
in classBaseOp
- Returns:
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doDiff
public List<SDVariable> doDiff(List<SDVariable> grad)
Description copied from class:DifferentialFunction
The actual implementation for automatic differentiation.- Specified by:
doDiff
in classDifferentialFunction
- Returns:
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