Class Norm1
- 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.Norm1
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- All Implemented Interfaces:
Op
,ReduceFloatOp
,ReduceOp
public class Norm1 extends BaseReduceFloatOp
Sum of absolute values- Author:
- Adam Gibson
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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 Norm1()
Norm1(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
Norm1(SameDiff sameDiff, SDVariable i_v, boolean keepDims, SDVariable dimensions)
Norm1(SameDiff sameDiff, SDVariable input, int... dimensions)
Norm1(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims)
Norm1(SameDiff sameDiff, SDVariable input, SDVariable dimensions)
Norm1(SameDiff sameDiff, SDVariable input, SDVariable dimensions, boolean keepDims)
Norm1(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
Norm1(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions)
Norm1(INDArray x, boolean keepDims, int... dimensions)
Norm1(INDArray x, int... dimensions)
Norm1(INDArray in, int[] dimensions, boolean keepDims)
Norm1(INDArray in, INDArray dimensions, boolean keepDims)
Norm1(INDArray input, INDArray output, boolean keepDims, int... dimensions)
Norm1(INDArray x, INDArray z, int... dimensions)
Norm1(INDArray x, INDArray y, INDArray z, boolean keepDims, int... dimensions)
Norm1(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.INDArray
noOp()
Returns the no op version of the input Basically when a reduce can't happen (eg: sum(0) on a row vector) you have a no op state for a given reduction.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, 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, setDimensions
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Constructor Detail
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Norm1
public Norm1(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
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Norm1
public Norm1(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
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Norm1
public Norm1(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims)
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Norm1
public Norm1(SameDiff sameDiff, SDVariable input, int... dimensions)
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Norm1
public Norm1(SameDiff sameDiff, SDVariable i_v, boolean keepDims, SDVariable dimensions)
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Norm1
public Norm1(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions)
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Norm1
public Norm1(SameDiff sameDiff, SDVariable input, SDVariable dimensions, boolean keepDims)
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Norm1
public Norm1(SameDiff sameDiff, SDVariable input, SDVariable dimensions)
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Norm1
public Norm1()
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Norm1
public Norm1(INDArray x, int... dimensions)
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Norm1
public Norm1(INDArray x, boolean keepDims, int... dimensions)
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Norm1
public Norm1(INDArray in, int[] dimensions, boolean keepDims)
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Method Detail
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noOp
public INDArray noOp()
Description copied from interface:ReduceOp
Returns the no op version of the input Basically when a reduce can't happen (eg: sum(0) on a row vector) you have a no op state for a given reduction. For most accumulations, this should return x but certain transformations should return say: the absolute value- Specified by:
noOp
in interfaceReduceOp
- Overrides:
noOp
in classBaseReduceOp
- Returns:
- the no op version of the input
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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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